Agentic AI Data Scientist/Engineer

Agentic AI Data Scientist/Engineer 1Lead to head up the team responsible for designing, building, and deploying agents and multi-agent workflows on our client's Multi-Agentic Platform. You'll lead a group of engineers/data scientists across the full agent lifecycle orchestration, LLM and prompt engineering, system integration, and evaluation while staying hands-on with architecture and technical direction.This role sits at the intersection of applied AI engineering and data science, and requires someone who can both lead a team and dive deep into agent design, orchestration frameworks, and LLM behavior.Required Qualifications :- 8+ years in software/ML engineering or data science, including recent hands-on experience building LLM-powered or agentic systems in production.- Strong Python engineering skills production-quality code, testing, packaging, and API design.- Hands-on experience with agent orchestration frameworks, especially LangGraph (LangChain, AutoGen, CrewAI, or Semantic Kernel also relevant).- Deep understanding of LLM fundamentals: prompt engineering, context management, tool/function calling, RAG, embeddings, and model selection tradeoffs.- Experience designing and implementing evaluation frameworks for LLM/agent outputs (offline eval sets, human-in-the-loop review, automated scoring/LLM-as-judge techniques, regression testing).- Solid data science fundamentals statistics, experimentation, model evaluation methodology and ability to apply them to non-deterministic AI systems.- Prior experience leading a team of engineers or data scientists technical mentorship, code/design review, and delivery ownership.- Experience integrating AI systems with external APIs, databases, and enterprise data sources.- Strong communication skills able to explain agent architecture and tradeoffs to both technical teams and business stakeholders.Preferred Qualifications :- Experience with multiple LLM providers/APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) and model routing/fallback strategies.- Experience with vector databases and RAG pipelines (e.g., Pinecone, OpenSearch, pgvector, FAISS).- Familiarity with AWS-based deployment of AI workloads (Lambda, ECS/EKS, SageMaker, Bedrock).- Experience building observability/tracing tooling for agentic systems (e.g., LangSmith, custom tracing, OpenTelemetry).- Background in consulting or client-facing delivery environments, managing scope and stakeholder expectations.- Experience with multi-agent design patterns (planner/executor, supervisor/worker, hierarchical agents, tool-routing agents).- Prior experience partnering with front-end/UI engineering teams to expose agent configuration and monitoring through a self-service interface. (ref:hirist.tech) Agentic AI Data Scientist/Engineer 1Lead to head up the team responsible for designing, building, and deploying agents and multi-agent workflows on our client's Multi-Agentic Platform. You'll lead a group of engineers/data scientists across the full agent lifecycle orchestration, LLM and prompt engineering, system integration, and evaluation while staying hands-on with architecture and technical direction.This role sits at the intersection of applied AI engineering and data science, and requires someone who can both lead a team and dive deep into agent design, orchestration frameworks, and LLM behavior.Required Qualifications :- 8+ years in software/ML engineering or data science, including recent hands-on experience building LLM-powered or agentic systems in production.- Strong Python engineering skills production-quality code, testing, packaging, and API design.- Hands-on experience with agent orchestration frameworks, especially LangGraph (LangChain, AutoGen, CrewAI, or Semantic Kernel also relevant).- Deep understanding of LLM fundamentals: prompt engineering, context management, tool/function calling, RAG, embeddings, and model selection tradeoffs.- Experience designing and implementing evaluation frameworks for LLM/agent outputs (offline eval sets, human-in-the-loop review, automated scoring/LLM-as-judge techniques, regression testing).- Solid data science fundamentals statistics, experimentation, model evaluation methodology and ability to apply them to non-deterministic AI systems.- Prior experience leading a team of engineers or data scientists technical mentorship, code/design review, and delivery ownership.- Experience integrating AI systems with external APIs, databases, and enterprise data sources.- Strong communication skills able to explain agent architecture and tradeoffs to both technical teams and business stakeholders.Preferred Qualifications :- Experience with multiple LLM providers/APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) and model routing/fallback strategies.- Experience with vector databases and RAG pipelines (e.g., Pinecone, OpenSearch, pgvector, FAISS).- Familiarity with AWS-based deployment of AI workloads (Lambda, ECS/EKS, SageMaker, Bedrock).- Experience building observability/traci