Lead Software Engineer
Equifax Inc. (company site, opens in a new tab)8+ yrsTrivandrumOn-siteDirect career pageEst. 30–45 LPA
Posted 1d ago
Reach people at Equifax Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Equifax Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design, development, and deployment of autonomous, multi-agent AI systems for complex enterprise environments, focusing on stateful workflows, multi-step planning, and tool interfacing.
- Own production-grade code for LLM orchestration layers including context-window optimization, semantic guardrails to prevent hallucinations and security risks, and latency/cost management.
- Lead an engineering squad establishing standards via Architectural Decision Records, pair programming, code reviews, and sprint planning collaboration.
Minimum Requirements
- 8+ years of core software engineering experience with at least 2+ years in production-grade LLM or Generative AI systems development.
- Expert proficiency in Python (including FastAPI/Pydantic) and experience with vector databases.
- Hands-on experience with multi-agent orchestration frameworks and containerization technologies (Docker, Kubernetes) with cloud-native AI deployment on AWS, Azure, or GCP.
- Deep understanding of non-deterministic system testing, state management, semantic guardrails, and prompt security mechanisms.
Ideal Candidate Profile
- Experienced in building multi-agent AI orchestration systems capable of reasoning and multi-step task management with robust security and observability.
- Comfortable leading engineering squads through architectural standards and agile development processes in enterprise AI contexts.
- Preferably has exposure to regulated industries such as FinTech or Financial Services and experience with multi-tenant AI platforms and enterprise fine-tuning or embedding training techniques.