Role Match
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Target role · career profile

Agents that reason, retrieve, verify, and recover

GenAI / Agentic AI Engineer

My path into agentic AI is grounded in building systems around the model, not treating a prompt as the product. Across two in-progress agent workflows, I am applying typed state, hybrid retrieval, bounded self-correction, source-aware evaluation, and human review so generated answers remain inspectable and useful.

Why this direction fits

I bring a backend-first approach to agentic systems: explicit contracts, controlled tool access, observable execution, and evaluation against defined targets.

Current evidence

BCA in Information Technology, IIT Dharwad-aligned NSQF L5.0 training, Oracle Data Science Professional, and an in-progress multi-agent research system.

01 / CAPABILITY MAP

How I would contribute

Orchestration

Stateful LangGraph workflows with planner, retriever, fact-checker, and correction loops.

Grounding

Hybrid retrieval with Qdrant or Chroma, BM25, schema context, and structured fallbacks.

Guardrails

Pydantic contracts, PII redaction, prompt-injection checks, read-only tools, and bounded retries.

Evaluation

Faithfulness, relevancy, context recall, tracing, and target-based regression checks.

02 / VERIFIED SKILLS

Role-aligned toolkit

  • Python 3.13
  • LangGraph
  • LangChain v1
  • FastAPI
  • Qdrant
  • Chroma
  • BM25
  • Pydantic v2
  • Langfuse
  • Docker

03 / SELECTED WORK

Evidence for this role

In progress01

Enterprise Multi-Agent Knowledge & Research Assistant

A cyclical Planner, Retriever, and Fact-Checker workflow combining hybrid and vectorless RAG with enterprise guardrails.

  • Target: 34% lower context hallucination
  • Evaluate: faithfulness · relevancy · recall
View case study
In progress05

Self-Healing BI & SQL Analytics Agent

A read-only analytics agent that inspects schemas, generates and validates SQL, self-corrects failures, and creates reviewed insights.

  • Target: self-correction within three retries
  • Safety: read-only execution · human review
View case study
In progress02

High-Throughput Asynchronous AI Gateway & Task Engine

An asynchronous gateway with distributed tasks, provider fallback, token-bucket limits, deduplication, and auditable usage.

  • Target: 250+ concurrent requests
  • Target: sub-50ms queue latency · >80% coverage
View case study

04 / TAILORED RESUME

Resume for this role

GenAI / Agentic AI Engineer

This version will foreground the experience and project evidence most relevant to this hiring path.

  • —Agent orchestration and self-correcting workflows
  • —Retrieval, grounding, and output validation
  • —LLM evaluation, safety, and observability
Download tailored resume