Agentic Software Engineer-II

Job description

Equifax is looking for a hands-on Agentic AI Engineer to join our enterprise AI Platform team in Trivandrum. Working under the guidance of Lead Agentic Architects, you will build, test, and deploy autonomous AI agents capable of reasoning, multi-step planning, tool utilization, and execution in enterprise environments. In this role, you will transition AI prototypes into resilient production systems focusing on writing clean, performant code, optimizing LLM prompts, integrating APIs, and managing stateful agentic workflows.

What You’ll Do

Implement stateful, multi-step agent behaviors using frameworks like LangGraph, AutoGen, or LlamaIndex. Optimize prompts using techniques like Chain-of-Thought (CoT) and ReAct. Develop resilient API wrappers and strict JSON schemas for LLM tool-calling/function-calling, connecting agents safely to internal databases, CRMs, and enterprise systems. Build context retention systems using short-term memory buffers and long-term vector/relational storage for multi-turn user interactions.

Build and maintain high-throughput ingestion pipelines; optimize search relevance using hybrid search, embeddings tuning, and re-ranking algorithms. Implement error handling and retry mechanisms for rate limits, API failures, and hallucinations, enabling agents to self-correct or cleanly escalate to human operators. Write deterministic software tests and LLM-as-a-judge evaluations. Utilize tracing tools (e.g., LangSmith, Phoenix) to debug reasoning paths, eliminate infinite loops, and optimize latency.

What Experience You Need 3-6 years of core software engineering experience, with at least 1+ years hands-on experience building and deploying production-grade LLM applications, RAG pipelines, or Agentic workflows. Strong proficiency in Python (FastAPI, Pydantic, Asyncio) and hands-on experience with LLM orchestration frameworks (LangGraph, LangChain, AutoGen, or LlamaIndex). Experience writing JSON schemas for function calling, building REST/gRPC API wrappers, and working with vector databases Experience using observability platforms for tracing agent execution, latency monitoring, and prompt evaluation.

Solid background in CI/CD, Git workflows, unit/integration testing, Docker containerization, and writing clean, scalable software. What Could Set You Apart Hands-on experience with cloud-native AI services on GCP (Vertex AI, ADK, Model Armour) Exposure to semantic guardrails framework (e.g., NeMo Guardrails, Guardrails AI). Familiarity with fine-tuning techniques, embedding customization, or open-source local model deployment