Software Engineer II

Equifax, Inc.; Thiruvananthapuram; In loco; INR 1.200.000 - 2.400.000; Tempo pieno

Descrizione del lavoro

Equifax is seeking a hands-on Agentic AI Engineer to join the enterprise AI Platform team in Trivandrum. You will build, test, and deploy autonomous AI agents capable of reasoning, multi-step planning, tool utilization, and execution in enterprise environments.

You will transition AI prototypes into resilient production systems with clean, performant code and robust prompts. You will work with LangGraph, LangChain, AutoGen, and LlamaIndex to implement stateful agents, APIs, and vector storage,

Competenze

• 3–6 years of software engineering experience.
• At least 1 year building and deploying production-grade LLM apps, RAG pipelines, or agentic workflows.
• Strong proficiency in Python (FastAPI, Pydantic, Asyncio).
• Experience with LLM orchestration frameworks (LangGraph, LangChain, AutoGen, or LlamaIndex).
• Experience writing JSON schemas for function calling and API wrappers.
• Familiarity with vector databases and observability/tracing tools.
• CI/CD, Docker, and scalable software practices.

Mansioni

• Implement multi-step agent behaviors using LangGraph, LangChain, AutoGen, or LlamaIndex.
• Develop REST/gRPC API wrappers and JSON schemas for tool-calling and internal DB connections.
• Build context retention systems with short-term memory and long-term storage.
• Create high-throughput ingestion pipelines and optimize search relevance.
• Implement error handling, retries, and self-correcting mechanisms.
• Write deterministic tests and use tracing tools to optimize latency.

Conoscenze

Python

LangGraph

LangChain

AutoGen

LlamaIndex

Pydantic

Asyncio

JSON schemas

API wrappers

Vector databases

CI/CD

Docker

Strumenti

Docker

REST/gRPC

Git

Descrizione del lavoro

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 escalat[e] 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