GenAI/Python Senior Engineer

Skills

• 5+ years of advanced professional Python development experience with production-grade coding practices
• Strong hands-on experience writing clean, tested, maintainable code using typing, pytest, packaging standards, Git, CI/CD, Docker, and code review discipline
• 1.5+ years of hands-on experience building GenAI / LLM applications in production using OpenAI, Azure OpenAI, Anthropic, Bedrock, or similar model APIs
• Experience building LLM-powered agents, including intent classification, domain-specific agents, agentic extraction flows, and multi-step orchestration
• Hands-on experience with Agentic AI frameworks or patterns such as LangChain, LangGraph, LlamaIndex, function calling, tool use, or custom orchestration
• Strong experience in structured output extraction from LLMs using JSON schema enforcement, Pydantic, retry/repair strategies, and validation logic
• Experience with RAG and vector search concepts including embeddings, chunking, hybrid search, reranking, entity resolution, fuzzy matching, confidence thresholds, and disambiguation flows
• Working knowledge of vector databases or search platforms such as pgvector, Pinecone, Weaviate, OpenSearch, Snowflake vector functions, or equivalent
• Strong API development experience using FastAPI or similar frameworks such as Flask or Django
• Experience with async Python and orchestration of parallel LLM/API calls
• Strong SQL skills and comfort working with large analytical datasets
• Cloud environment experience, preferably Azure; AWS or GCP acceptable
• Strong written and verbal communication skills, with ability to collaborate directly with engineering teams, product owners, and cross-functional stakeholders

Responsibilities

• Build and enhance LLM-powered agentic applications using Python
• Develop intent classification, domain-specialist agent workflows, and agentic extraction pipelines for complex user questions
• Build natural-language-to-structured-payload pipelines that convert user utterances into accurate JSON query payloads, including filters, exclusions, rankings, and metric selection
• Integrate semantic search and vector retrieval services for embedding-based entity resolution, fuzzy matching, confidence scoring, and disambiguation flows
• Design, build, and consume FastAPI-based microservices
• Implement async orchestration patterns for parallel LLM calls, API calls, and downstream service integrations
• Develop prompt engineering patterns, structured output enforcement, JSON schema validation, function calling, tool usage, and guardrails
• Build evaluation harnesses, test sets, and regression test frameworks to measure extraction accuracy and validate prompt/model changes
• Work with metadata/catalog services, entitlement-aware data access, and reporting-engine payload contracts
• Collaborate with multiple platform, data, service, and product teams to deliver production-ready GenAI capabilities
• Write clear technical documentation including Confluence pages, ADRs, sequence diagrams, and flow diagrams
• Participate in hands-on technical evaluation, code reviews, design discussions, and production readiness reviews

Pay

$90,000–$130,000 a year

Benefits

• Discretionary Annual Incentive
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans
• Family Support: Maternal & Parental Leaves
• Insurance Options: Auto & Home Insurance, Identity Theft Protection
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement
• Time Off: Vacation, Time Off, Sick Leave & Holidays
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing