Lead Software Engineer - Remote

Primary Responsibilities

• Agentic AI Architecture & Delivery
  • Design and implement (multi) agentic workflows where LLMs plan, decompose tasks, invoke tools/APIs, and synthesize answers across heterogeneous data sources and services
  • Build retrieval augmented generation (RAG) and hybrid search pipelines to power robust question answering over clinical and operational data
  • Design, code, test, document, and maintain high quality, scalable Big Data and cloud solutions
  • Develop scalable microservices and APIs for integrating agent capabilities into clinician tools and internal apps
  • Create prototypes/POCs and conduct design/code reviews to derisk delivery and raise engineering quality
• LLMs, GenAI & Model Adaptation
  • Leverage and adapt LLMs; perform prompt engineering, grounding, guard railing, and domain adaptation for healthcare terminology and tasks
  • Design intelligent frameworks and finetune models for compliance, accuracy, and ethical standards
  • Establish evaluation frameworks (automatic + human in the loop) to measure faithfulness, helpfulness, bias, toxicity, privacy leakage, and overall quality
• Data & Platform Engineering
  • Partner with data engineering to build feature/retrieval stores, embeddings pipelines, and ETL/ELT jobs on Spark/Databricks; design analytics models and rules engines
  • Define and develop APIs for integrations across the enterprise; improve data access patterns for low latency inference
• Delivery, MLOps & Reliability
  • Own MLOps/LLMOps: CI/CD for models/prompts, automated tests (unit/contract/eval), versioning, lineage, rollback; enable blue/green or canary releases
  • Instrument SLOs/SLIs (latency, availability, hallucination/defect rate) and cost KPIs (tokens, GPU hours) with dashboards and alerts
  • Lead production deployments on internal platforms (e.g., UAIS) with solid observability, reliability, and cost controls
• Security, Privacy & Compliance
  • Champion HIPAA and regulated industry controls; integrate access controls, PHI/PPI safeguards, data minimization, encryption, and auditability
  • Collaborate with legal, compliance, and clinical safety to operationalize Responsible AI principles
• Product, Estimation & Collaboration
  • Analyze and define customer requirements; assist in defining product technical architecture and delivery roadmaps
  • Provide effort estimates and inputs for resource planning; collaborate with QA, architecture, and peer teams
  • Write technical documentation, support production, and mentor engineers, and keep skills current through continuous learning

Required Qualifications

• Bachelor's degree in Engineering, Computer Science, IT, or related fields
• 10+ years of total technology experience
• 8+ years hands on software development/data engineering/analytics with solid AI/ML delivery (Azure preferred) with Scala, Python, PySpark
• 4+ years hands on with Databricks
• 4+ years with ADF/Airflow (orchestration/scaling)
• 4+ years with big data & streaming (Hadoop, MapReduce/HDFS, Spark, Kafka); Docker/Kubernetes
• 4+ years with MySQL and NoSQL databases
• 4+ years with Agile/Scrum, GitHub, Jenkins CI/CD, JUnit; solid coding standards and code reviews
• 2+ years with LLMs & GenAI (Langchain, LangGraph, RAG, Vector DB, Azure Open AI, MCP Server, Agents, LangFuse)
• 2+ years of experience with container (Docker/Kubernetes)
• 1+ years with Proficiency building services or full stack apps (e.g., FastAPI/Flask, Node.js, React/Angular, TypeScript, HTML/CSS)

Preferred Qualifications

• Healthcare experience; familiarity with clinical datasets
• Experience working in regulated industries, with knowledge of ethical AI/ML practices and compliance requirements
• SOA and enterprise integration concepts
• Publications/patents or notable open-source contributions
• Proven excellent analysis, problem solving, and communication skills