Lead Software Engineer

Equifax, Inc.; Thiruvananthapuram; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

Equifax India is seeking a Lead Software Engineer to serve as the technical anchor and hands‑on architect for our enterprise Agentic AI platform. You will design, build, and deploy autonomous, multi‑agent architectures capable of reasoning, multi‑step planning, tool selection, and robust execution.

In this role, you will lead an engineering squad, establish core engineering standards for AI application development, and write critical‑path production code to ensure our AI agents perform safely,

Qualifications

• 8+ years in core software engineering with hands-on AI systems.
• At least 2+ years building and deploying production-grade LLM applications.
• Hands-on experience with multi-agent orchestration frameworks and tooling.

Responsibilities

• Architect and build stateful multi-agent workflows with patterns like ReAct and Plan-and-Solve.
• Build secure interfaces for LLM function-calling across databases, ERPs, and CRMs.
• Write production-grade code for orchestration, routing, and performance optimization.

Skills

Python

Agent frameworks

Docker

Kubernetes

AWS/Azure/GCP

LLM applications

FastAPI

Pydantic

Vector databases

Tools

FastAPI

Pydantic

Vector databases

Job description

Equifax India is seeking a Lead Software Engineer to serve as the technical anchor and hands‑on architect for our enterprise Agentic AI platform. Moving beyond standard chatbots and retrieval systems, you will design, build, and deploy autonomous, multi‑agent architectures capable of reasoning, multi‑step planning, tool selection, and robust execution.

In this role, you will lead an engineering squad, establish core engineering standards for AI application development, and write critical‑path production code to ensure our AI agents perform safely, deterministically, and efficiently at scale in complex enterprise environments.

What You’ll Do

• Architect and build stateful multi‑agent workflows (using ReAct, Plan‑and‑Solve patterns) where specialized LLM agents delegate tasks, manage short/long‑term memory, and synthesize results.
• Build robust, idempotent, and secure interfaces for LLM function‑calling across enterprise software databases, ERPs, and CRMs.
• Write clean, highly performant production code for the core orchestration layer, context‑window optimization (routing, chunking, compression), and latency/cost management.
• Implement deterministic semantic guardrails around LLM outputs to prevent hallucinations, prompt injection, and unauthorized API/tool calls.
• Establish automated evaluation pipelines (LLM‑as‑a‑judge, deterministic testing) and deep tracing observability to monitor multi‑step agent reasoning and prevent infinite loops in production.
• Guide an engineering squad through Architectural Decision Records (ADRs), pair programming, and code reviews while partnering with Delivery Managers on sprint planning.

What Experience You Need

• 8+ years of core software engineering experience, with at least 2+ years building and deploying production‑grade LLM applications / Generative AI systems.
• Hands‑on experience with multi‑agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or custom graph‑based agent state machines).
• Expert proficiency in Python (FastAPI/Pydantic) and experience with vector databases
• Deep understanding of non‑deterministic system testing, state management, semantic guardrails (e.g., Guardrails AI, NeMo Guardrails), and prompt security.
• Hands‑on experience with containerization (Docker, Kubernetes) and deploying cloud‑native AI solutions on AWS, Azure, or GCP.

What Could Set You Apart )

• Prior experience building multi‑tenant AI platforms in regulated industries (FinTech, Financial Services, Data Analytics).
• Contributions to open‑source LLM/Agentic frameworks or publications in applied AI/ML.
• Hands‑on knowledge of enterprise fine‑tuning, PEFT/LoRA, or custom embedding model training.