Senior/Lead Data Scientist / AIML Engineer/ AI Automation Engineer
for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map content.
We have job description: includes About Naveera Technology LLC (company description). That could be "About the role"? Actually "About the role" is typical heading for role overview. We have "Role Overview". Also we have "Key Responsibilities". Then "Tasks Required Skills" (looks like skills list). Then "Preferred Qualifications". Then "Nice to Have". Then "Benefits". No explicit Pay or Schedule except shift time: "Shift: 2:00 PM 11:30 PM IST". That's schedule info. So we can include Schedule section with that shift. Pay not mentioned, so omit.
We need to avoid repeating job title as heading. Use headings for sections only.
We need to preserve all substantive info, remove boilerplate like greeting, LinkedIn, etc. Also remove "Greetings of the day!! I am Arumugam Veera..." etc. Also remove application instructions etc.
We need to include About Naveera Technology LLC as maybe "About the company"? But headings list only includes About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. No "About the company". Could we put company description under About the role? Probably not. But we could include a brief paragraph under About the role (role overview) and maybe include company description as part of that? The instruction: "Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It says e.g., meaning those are examples, but we should use those headings when appropriate. It doesn't forbid other headings? It says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Likely they expect us to use those headings only. So we need to map content to those headings.
Thus:
- About the role: could contain Role Overview and maybe company description? But About the role likely describes the role, not company. However we have Role Overview paragraph. We'll put that.
- Responsibilities: Key Responsibilities list.
- Requirements: maybe Preferred Qualifications? Or Requirements? The posting has "Preferred Qualifications" and "Nice to Have". Could treat "Requirements" as Preferred Qualifications (must-have). We'll put Preferred Qualifications under Requirements.
- Qualifications: maybe Nice to Have? Or we could split: Requirements = Preferred Qualifications, Qualifications = Nice to Have. But we need to avoid filler. We'll include both if content.
- Skills: Tasks Required Skills list.
- Benefits: Benefits list.
- Schedule: Shift info.
- Pay: not present, omit.
We must not include empty sections.
Now we need to format lists with - . For prose use
.
We need to preserve all substantive info: include company description? Where to put? If we omit, we lose info. But maybe we can include company description under About the role as part of role overview? The instruction says preserve ALL substantive information. So we need to include company description somewhere. Could add a paragraph under About the role before role overview? But About the role heading is for role, not company. However we could treat About the role as including both company and role? Might be acceptable.
Alternatively we could add a separate heading like "About Naveera Technology LLC" but not in allowed list. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't strictly forbid other headings, but says "Use for section headings (e.g. ...)" implying those are examples; we could still use other headings if needed. However they also say "Prefer a few substantive sections over many thin ones." So maybe we should stick to those headings.
We could embed company description in a
under About the role heading, as part of the role context. That would preserve it.
Thus:
About the role
[company description] [role overview]
But we need to separate maybe two paragraphs.
Let's extract company description:
"Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing"
That's a bit run-on; we can keep as paragraph.
Role Overview: "We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams."
We'll combine.
Now Responsibilities: list items from "Key Responsibilities". We'll extract each sentence starting with a verb.
List:
- Lead the architecture and development of AI-driven automation platforms and intelligent workflows.
- Build scalable Python backend services (REST APIs, asynchronous processing, microservices).
- Design workflow orchestration using Temporal (or equivalent workflow engines) for long-running business processes.
- Develop AI Agents using modern LLM frameworks and AWS AI services.
- Integrate Python services with C#/.NET applications, enterprise systems, and external APIs.
- Design secure, scalable, stateful/stateless backend architectures with event-driven patterns.
- Implement authentication and authorization (OAuth2, JWT, SSO, RBAC/ABAC).
- Develop AI-powered healthcare workflows across RCM, enrollment, claims, payer/provider integrations, and document automation.
- Build Full Stack AI applications including backend APIs, workflow services, AI orchestration, and frontend integration.
- Implement AI Ops practices including monitoring, observability, model lifecycle management, logging, evaluation, and production support.
- Drive engineering best practices, code quality, CI/CD, documentation, and mentor development teams.
Now Skills: "Tasks Required Skills" list includes many items grouped. We'll extract each bullet.
We have categories: Backend Engineering, Workflow & Automation, AI & Automation, Security, Cloud & AI Ops, Databases.
We'll create a flat list of skills.
List:
- Python (Expert)
- FastAPI, Flask or Django
- REST APIs, WebSockets, Async Programming
- Microservices architecture
- External API integrations
- C#/.NET integration experience
- Temporal (Preferred) or equivalent workflow orchestration
- Event-driven architecture
- Distributed processing
- Long-running workflow management
- State management
- AI Agent frameworks (CrewAI, AutoGen, Semantic Kernel, LangGraph, etc.)
- LLM integration (Amazon Bedrock/OpenAI/Azure OpenAI)
- Prompt Engineering
- Guardrails
- RAG Architecture
- Vector Databases (ChromaDB, Pinecone, pgvector)
- MCP (Model Context Protocol) and AI Skills/Tooling knowledge
- Security: OAuth2, JWT, SSO, RBAC / ABAC
- API Security
- Secrets Management
- Cloud & AI Ops: AWS (Preferred) or Azure
- Docker
- Git
- CI/CD Pipelines
- Monitoring & Logging
- AI Ops, Model Monitoring, Observability
- Production Deployment & Support
- Databases: SQL Server / PostgreSQL / Redshift
- Redis
- NoSQL Databases
- Vector Databases (again but okay)
We could deduplicate but fine.
Now Requirements (Preferred Qualifications):
- Experience building enterprise AI automation platforms.
- Healthcare domain knowledge with Revenue Cycle Management (RCM), Claims, Eligibility, Enrollment, Prior Authorization, or Provider/Payer workflows.
- Strong understanding of distributed systems and scalable backend architecture.
- Experience integrating AI solutions into existing enterprise applications.
- Strong debugging, architecture, and problem-solving skills.
- Experience leading technical teams, conducting code reviews, and mentoring engineers.
- Experience delivering production-grade Full Stack AI applications.
Now Qualifications (Nice to Have):
- Kubernetes
- Kafka / RabbitMQ
- GraphQL
- Playwright / Browser Automation
- Terraform / Infrastructure as Code
- Snowflake, Databricks
- MLflow or Model Lifecycle Management
- React or modern frontend frameworks
- Healthcare interoperability standards (FHIR/HL7)
Now Benefits:
- Flexible Remote/Hybrid work environment.
- Exposure to global enterprise customers.
- Collaborative, innovation-driven engineering culture.
- Continuous learning and certification opportunities.
Now Schedule:
- Shift: 2:00 PM 11:30 PM IST
We'll put as Shift: 2:00 PM 11:30 PM IST
under Schedule heading.
Now ensure no boilerplate: remove greeting, LinkedIn, etc. Also remove "Job Title: Senior/Lead Data Scientist / AIML Engineer/ AI Automation Engineer Experience: 7 to 15 Years Shift: 2:00 PM 11:30 PM IST Job Type: Full-Time Mode: If the resource from India then preferrbly Working from Office". We already used shift; we can drop other metadata.
Now produce HTML fragment.
We need to wrap each section in heading then content.
We'll output:
About the role
Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing.
We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams.
Responsibilities
- Lead the architecture and development of AI-driven automation
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Likely they expect us to use those headings only. So we need to map content to those headings.
Thus:
- About the role: could contain Role Overview and maybe company description? But About the role likely describes the role, not company. However we have Role Overview paragraph. We'll put that.
- Responsibilities: Key Responsibilities list.
- Requirements: maybe Preferred Qualifications? Or Requirements? The posting has "Preferred Qualifications" and "Nice to Have". Could treat "Requirements" as Preferred Qualifications (must-have). We'll put Preferred Qualifications under Requirements.
- Qualifications: maybe Nice to Have? Or we could split: Requirements = Preferred Qualifications, Qualifications = Nice to Have. But we need to avoid filler. We'll include both if content.
- Skills: Tasks Required Skills list.
- Benefits: Benefits list.
- Schedule: Shift info.
- Pay: not present, omit.
We must not include empty sections.
Now we need to format lists with - . For prose use
.
We need to preserve all substantive info: include company description? Where to put? If we omit, we lose info. But maybe we can include company description under About the role as part of role overview? The instruction says preserve ALL substantive information. So we need to include company description somewhere. Could add a paragraph under About the role before role overview? But About the role heading is for role, not company. However we could treat About the role as including both company and role? Might be acceptable.
Alternatively we could add a separate heading like "About Naveera Technology LLC" but not in allowed list. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't strictly forbid other headings, but says "Use for section headings (e.g. ...)" implying those are examples; we could still use other headings if needed. However they also say "Prefer a few substantive sections over many thin ones." So maybe we should stick to those headings.
We could embed company description in a
under About the role heading, as part of the role context. That would preserve it.
Thus:
About the role
[company description] [role overview]
But we need to separate maybe two paragraphs.
Let's extract company description:
"Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing"
That's a bit run-on; we can keep as paragraph.
Role Overview: "We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams."
We'll combine.
Now Responsibilities: list items from "Key Responsibilities". We'll extract each sentence starting with a verb.
List:
- Lead the architecture and development of AI-driven automation platforms and intelligent workflows.
- Build scalable Python backend services (REST APIs, asynchronous processing, microservices).
- Design workflow orchestration using Temporal (or equivalent workflow engines) for long-running business processes.
- Develop AI Agents using modern LLM frameworks and AWS AI services.
- Integrate Python services with C#/.NET applications, enterprise systems, and external APIs.
- Design secure, scalable, stateful/stateless backend architectures with event-driven patterns.
- Implement authentication and authorization (OAuth2, JWT, SSO, RBAC/ABAC).
- Develop AI-powered healthcare workflows across RCM, enrollment, claims, payer/provider integrations, and document automation.
- Build Full Stack AI applications including backend APIs, workflow services, AI orchestration, and frontend integration.
- Implement AI Ops practices including monitoring, observability, model lifecycle management, logging, evaluation, and production support.
- Drive engineering best practices, code quality, CI/CD, documentation, and mentor development teams.
Now Skills: "Tasks Required Skills" list includes many items grouped. We'll extract each bullet.
We have categories: Backend Engineering, Workflow & Automation, AI & Automation, Security, Cloud & AI Ops, Databases.
We'll create a flat list of skills.
List:
- Python (Expert)
- FastAPI, Flask or Django
- REST APIs, WebSockets, Async Programming
- Microservices architecture
- External API integrations
- C#/.NET integration experience
- Temporal (Preferred) or equivalent workflow orchestration
- Event-driven architecture
- Distributed processing
- Long-running workflow management
- State management
- AI Agent frameworks (CrewAI, AutoGen, Semantic Kernel, LangGraph, etc.)
- LLM integration (Amazon Bedrock/OpenAI/Azure OpenAI)
- Prompt Engineering
- Guardrails
- RAG Architecture
- Vector Databases (ChromaDB, Pinecone, pgvector)
- MCP (Model Context Protocol) and AI Skills/Tooling knowledge
- Security: OAuth2, JWT, SSO, RBAC / ABAC
- API Security
- Secrets Management
- Cloud & AI Ops: AWS (Preferred) or Azure
- Docker
- Git
- CI/CD Pipelines
- Monitoring & Logging
- AI Ops, Model Monitoring, Observability
- Production Deployment & Support
- Databases: SQL Server / PostgreSQL / Redshift
- Redis
- NoSQL Databases
- Vector Databases (again but okay)
We could deduplicate but fine.
Now Requirements (Preferred Qualifications):
- Experience building enterprise AI automation platforms.
- Healthcare domain knowledge with Revenue Cycle Management (RCM), Claims, Eligibility, Enrollment, Prior Authorization, or Provider/Payer workflows.
- Strong understanding of distributed systems and scalable backend architecture.
- Experience integrating AI solutions into existing enterprise applications.
- Strong debugging, architecture, and problem-solving skills.
- Experience leading technical teams, conducting code reviews, and mentoring engineers.
- Experience delivering production-grade Full Stack AI applications.
Now Qualifications (Nice to Have):
- Kubernetes
- Kafka / RabbitMQ
- GraphQL
- Playwright / Browser Automation
- Terraform / Infrastructure as Code
- Snowflake, Databricks
- MLflow or Model Lifecycle Management
- React or modern frontend frameworks
- Healthcare interoperability standards (FHIR/HL7)
Now Benefits:
- Flexible Remote/Hybrid work environment.
- Exposure to global enterprise customers.
- Collaborative, innovation-driven engineering culture.
- Continuous learning and certification opportunities.
Now Schedule:
- Shift: 2:00 PM 11:30 PM IST
We'll put as Shift: 2:00 PM 11:30 PM IST
under Schedule heading.
Now ensure no boilerplate: remove greeting, LinkedIn, etc. Also remove "Job Title: Senior/Lead Data Scientist / AIML Engineer/ AI Automation Engineer Experience: 7 to 15 Years Shift: 2:00 PM 11:30 PM IST Job Type: Full-Time Mode: If the resource from India then preferrbly Working from Office". We already used shift; we can drop other metadata.
Now produce HTML fragment.
We need to wrap each section in heading then content.
We'll output:
About the role
Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing.
We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams.
Responsibilities
- Lead the architecture and development of AI-driven automation
. We need to preserve all substantive info: include company description? Where to put? If we omit, we lose info. But maybe we can include company description under About the role as part of role overview? The instruction says preserve ALL substantive information. So we need to include company description somewhere. Could add a paragraph under About the role before role overview? But About the role heading is for role, not company. However we could treat About the role as including both company and role? Might be acceptable. Alternatively we could add a separate heading like "About Naveera Technology LLC" but not in allowed list. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't strictly forbid other headings, but says "Use for section headings (e.g. ...)" implying those are examples; we could still use other headings if needed. However they also say "Prefer a few substantive sections over many thin ones." So maybe we should stick to those headings.
We could embed company description in a
under About the role heading, as part of the role context. That would preserve it. Thus:
About the role
[company description] [role overview]
But we need to separate maybe two paragraphs. Let's extract company description: "Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing" That's a bit run-on; we can keep as paragraph. Role Overview: "We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams." We'll combine. Now Responsibilities: list items from "Key Responsibilities". We'll extract each sentence starting with a verb. List: - Lead the architecture and development of AI-driven automation platforms and intelligent workflows. - Build scalable Python backend services (REST APIs, asynchronous processing, microservices). - Design workflow orchestration using Temporal (or equivalent workflow engines) for long-running business processes. - Develop AI Agents using modern LLM frameworks and AWS AI services. - Integrate Python services with C#/.NET applications, enterprise systems, and external APIs. - Design secure, scalable, stateful/stateless backend architectures with event-driven patterns. - Implement authentication and authorization (OAuth2, JWT, SSO, RBAC/ABAC). - Develop AI-powered healthcare workflows across RCM, enrollment, claims, payer/provider integrations, and document automation. - Build Full Stack AI applications including backend APIs, workflow services, AI orchestration, and frontend integration. - Implement AI Ops practices including monitoring, observability, model lifecycle management, logging, evaluation, and production support. - Drive engineering best practices, code quality, CI/CD, documentation, and mentor development teams. Now Skills: "Tasks Required Skills" list includes many items grouped. We'll extract each bullet. We have categories: Backend Engineering, Workflow & Automation, AI & Automation, Security, Cloud & AI Ops, Databases. We'll create a flat list of skills. List: - Python (Expert) - FastAPI, Flask or Django - REST APIs, WebSockets, Async Programming - Microservices architecture - External API integrations - C#/.NET integration experience - Temporal (Preferred) or equivalent workflow orchestration - Event-driven architecture - Distributed processing - Long-running workflow management - State management - AI Agent frameworks (CrewAI, AutoGen, Semantic Kernel, LangGraph, etc.) - LLM integration (Amazon Bedrock/OpenAI/Azure OpenAI) - Prompt Engineering - Guardrails - RAG Architecture - Vector Databases (ChromaDB, Pinecone, pgvector) - MCP (Model Context Protocol) and AI Skills/Tooling knowledge - Security: OAuth2, JWT, SSO, RBAC / ABAC - API Security - Secrets Management - Cloud & AI Ops: AWS (Preferred) or Azure - Docker - Git - CI/CD Pipelines - Monitoring & Logging - AI Ops, Model Monitoring, Observability - Production Deployment & Support - Databases: SQL Server / PostgreSQL / Redshift - Redis - NoSQL Databases - Vector Databases (again but okay) We could deduplicate but fine. Now Requirements (Preferred Qualifications): - Experience building enterprise AI automation platforms. - Healthcare domain knowledge with Revenue Cycle Management (RCM), Claims, Eligibility, Enrollment, Prior Authorization, or Provider/Payer workflows. - Strong understanding of distributed systems and scalable backend architecture. - Experience integrating AI solutions into existing enterprise applications. - Strong debugging, architecture, and problem-solving skills. - Experience leading technical teams, conducting code reviews, and mentoring engineers. - Experience delivering production-grade Full Stack AI applications. Now Qualifications (Nice to Have): - Kubernetes - Kafka / RabbitMQ - GraphQL - Playwright / Browser Automation - Terraform / Infrastructure as Code - Snowflake, Databricks - MLflow or Model Lifecycle Management - React or modern frontend frameworks - Healthcare interoperability standards (FHIR/HL7) Now Benefits: - Flexible Remote/Hybrid work environment. - Exposure to global enterprise customers. - Collaborative, innovation-driven engineering culture. - Continuous learning and certification opportunities. Now Schedule: - Shift: 2:00 PM 11:30 PM IST We'll put asShift: 2:00 PM 11:30 PM IST
under Schedule heading. Now ensure no boilerplate: remove greeting, LinkedIn, etc. Also remove "Job Title: Senior/Lead Data Scientist / AIML Engineer/ AI Automation Engineer Experience: 7 to 15 Years Shift: 2:00 PM 11:30 PM IST Job Type: Full-Time Mode: If the resource from India then preferrbly Working from Office". We already used shift; we can drop other metadata. Now produce HTML fragment. We need to wrap each section in heading then content.
We'll output:
About the role
Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value. With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices. From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms. Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing.
We are seeking an experienced AI Automation Engineer/Lead to design and build enterprise-grade AI automation platforms for Healthcare and Revenue Cycle Management (RCM). The ideal candidate will have strong expertise in Python backend development, workflow orchestration, AI agent frameworks, cloud-native architecture, and enterprise integrations. This role will lead the implementation of scalable AI solutions while mentoring engineers and collaborating with cross-functional teams.
Responsibilities
- Lead the architecture and development of AI-driven automation