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Agentic AI Engineering - Lead Programmer Analyst (Exp: 5 Yrs to 7 Yrs)

Agentic AI Engineering - Lead Programmer Analyst (Exp: 5 Yrs to 7 Yrs)

bilvantis technologies
5-7 Years
Not Disclosed
Early Applicant
  • Posted 19 days ago
  • Be among the first 20 applicants

Job Description

Job Description: Agentic AI Engineering - Lead Programmer Analyst (Exp: 5 Yrs to 7 Yrs)

Design and deliver LLM applications and agents that retrieve enterprise knowledge, use tools and complete business workflows reliably. Remain hands-on in architecture, implementation and debugging while guiding junior engineers. The role focuses on applications built with existing models; traditional predictive-model training is not a core requirement.

Required Experience And Technical Skills

  • 5+ years of professional software or data engineering experience, including hands-on delivery of LLM applications and agentic AI workflows.
  • Strong Python and SQL; API development with FastAPI or Flask, validation with Pydantic, and asynchronous service integration.
  • Practical experience with LLM APIs, streaming, token limits, prompt design, schema validation and model selection.
  • Hands-on LangChain experience or equivalent frameworks; ability to choose between fixed workflows and agent decisions.
  • RAG development using LangChain or LlamaIndex and vector stores such as pgvector or Qdrant, with filters and retrieval evaluation.
  • Ability to implement tool calling, persistent state, context and memory management, approval flows and reliable error handling.
  • Experience with AI evaluation, observability, access controls and secure tool execution, plus Git, testing, containers and cloud deployment.

Key Responsibilities

  • Translate business workflows into clear agent responsibilities, tool interfaces, success criteria and approval boundaries.
  • Build LLM applications using effective prompts, structured outputs and context management; choose models based on quality, latency and cost.
  • Develop RAG pipelines covering document ingestion, chunking, embeddings, hybrid retrieval, reranking and source-grounded answers.
  • Implement tool-using workflows with state, memory, checkpoints, human approvals, retries and safeguards against repeated actions or endless loops.
  • Integrate business APIs and data sources; enforce permissions and protect against prompt injection and sensitive-data exposure.
  • Build evaluation datasets, regression checks and traces; debug failures and improve task completion, response time and operating cost.
  • Own implementation quality and delivery while coaching juniors through design, coding, testing and production troubleshooting.

Mentoring And Technical Ownership

  • Demonstrated ability to groom and guide junior engineers through pairing, design discussions, code reviews and constructive feedback.
  • Define tasks and acceptance criteria, remove technical blockers and review individual progress toward independent delivery.
  • Build reusable agent components and practical documentation; explain design choices and delivery risks to stakeholders.

Preferred Skills

  • Exposure to CrewAI / LangGraph for agent orchestration and multi-agent workflows; MCP integration and multimodal applications.
  • Exposure to Langfuse, LangSmith or equivalent tracing and evaluation tools; prompt/version management and evaluation gates.
  • Hugging Face Transformers for open-model integration; caching and model routing. Frameworks listed are alternatives; mastery of every tool is not required.

More Info

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Key Skills

LangChain

pgvector

Qdrant

Pydantic

LlamaIndex

Containers

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5-7 yrs
Hyderabad, India
Skills:
cloud platform , Sql, Numpy, Git, Pandas, XGBoost, Flask, FastAPI, Containers, Python, LangChain, scikit-learn, LLM APIs, automated tests