Senior AI Engineer

One American Mortgage; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Employ is seeking a senior AI systems architect to lead the architecture and evolution of AI‑powered capabilities. You will design, build, and scale agents, RAG pipelines, and orchestration layers, while setting standards for safe, reliable AI across the platform.

You will shape how AI features are defined, evaluated, and deployed, guiding teams with high ownership and autonomy. Strong focus on production‑grade systems and governance is expected.

Qualifications

• 4+ years building AI‑augmented product capabilities (LLMs, RAG systems, agents, orchestration frameworks).
• Experience designing decoupled systems using event‑driven and asynchronous patterns such as Kafka, SQS, or BullMQ; implementing asynchronous workflows that prevent blocking operations in user‑facing systems.
• Experience persisting state across sessions, managing context windows efficiently, and handling concurrency and race conditions when multiple agents interact with shared data.
• Experience enforcing structured outputs using schema validation tools such as Pydantic, Zod, or JSON Schema to ensure AI‑generated outputs are reliable and machine‑readable.
• Strong understanding of REST, GraphQL, or RPC interface design, along with authentication, rate limiting, and idempotent API patterns.

Responsibilities

• Lead the architecture and delivery of end‑to‑end AI‑powered systems, including agents, RAG pipelines, orchestration layers, and reasoning workflows.
• Translate product vision into scalable technical systems.
• Define contracts, state management strategies, and guardrails for AI‑driven workflows.
• Own and evolve API contracts that AI systems interact with, ensuring reliability, idempotency, authentication safety, and rate limiting.
• Design schema enforcement and validation layers for AI‑generated outputs.
• Implement retries, fallback strategies, and failure‑mode containment.
• Establish evaluation frameworks for benchmarking, regression testing, and drift detection.
• Create observability standards for AI systems, including structured logging, telemetry, tracing, and performance monitoring.
• Productionize experimental AI capabilities into scalable, secure services.
• Establish architectural patterns and standards adopted across teams.
• Mentor engineers in AI‑native and spec‑driven development practices.
• Influence engineering culture through clarity, urgency, and execution.
• Decompose high‑level business outcomes into executable technical systems.

Skills

AI systems

Event-driven design

Asynchronous workflows

Schema validation

API design

Tools

Kafka

SQS

BullMQ

LangChain

Pydantic

Job description

About the Role

In this senior‑level role, you will lead the architecture and evolution of AI‑powered systems that transform probabilistic model outputs into reliable, production‑grade product capabilities. You will design and ship systems around agents, retrieval pipelines, orchestration layers, and evaluation frameworks, while defining the architectural standards that ensure AI‑driven features operate safely and at scale across our platform.

This is not a feature‑delivery role — it is a systems‑definition role. Your decisions will shape how AI capabilities are built, evaluated, and deployed across the organization.

About the Team

Our AI Foundation team is building the foundation for how AI will power the next generation of products at Employ. This is a high‑ownership, high‑autonomy team responsible for turning rapidly evolving model capabilities into reliable, customer‑facing systems.

What You’ll Do

• Lead the architecture and delivery of end‑to‑end AI‑powered systems, including agents, RAG pipelines, orchestration layers, and reasoning workflows.
• Translate product vision into scalable technical systems.
• Define contracts, state management strategies, and guardrails for AI‑driven workflows.
• Own and evolve API contracts that AI systems interact with, ensuring reliability, idempotency, authentication safety, and rate limiting.
• Design schema enforcement and validation layers for AI‑generated outputs.
• Implement retries, fallback strategies, and failure‑mode containment.
• Establish evaluation frameworks for benchmarking, regression testing, and drift detection.
• Create observability standards for AI systems, including structured logging, telemetry, tracing, and performance monitoring.
• Productionize experimental AI capabilities into scalable, secure services.
• Establish architectural patterns and standards adopted across teams.
• Mentor engineers in AI‑native and spec‑driven development practices.
• Influence engineering culture through clarity, urgency, and execution.
• Decompose high‑level business outcomes into executable technical systems.

What You Bring

You have mastered the fundamentals of software engineering and operate at a higher level of abstraction. You are not simply accepting AI‑generated code — you review, restructure, and integrate it into cohesive, production‑grade systems.

• 4+ years building AI‑augmented product capabilities (LLMs, RAG systems, agents, orchestration frameworks).
• Experience designing decoupled systems using event‑driven and asynchronous patterns such as Kafka, SQS, or BullMQ; implementing asynchronous workflows that prevent blocking operations in user‑facing systems.
• Experience persisting state across sessions, managing context windows efficiently, and handling concurrency and race conditions when multiple agents interact with shared data.
• Experience enforcing structured outputs using schema validation tools such as Pydantic, Zod, or JSON Schema to ensure AI‑generated outputs are reliable and machine‑readable.
• Strong understanding of REST, GraphQL, or RPC interface design, along with authentication, rate limiting, and idempotent API patterns.

Tech Stack & Hard Skills

Languages: Python, including asyncio, decorators, and the modern Python ecosystem. TypeScript / Node for integration and application‑layer logic.

AI stack: Orchestration frameworks such as LangChain, LangGraph, or custom agent loops. Retrieval‑Augmented Generation (RAG) systems. Hybrid search, re‑ranking, and chunking strategies. Vector databases such as Pinecone, pgvector, or Weaviate.

Database & infrastructure: Advanced SQL skills including query optimization and indexing strategies. Containerization using Docker, Kubernetes, or similar orchestration platforms. Experience running isolated environments for code execution.

Compensation & Benefits

Your final offer will consider your unique skills, experience, and location. In addition to base salary, total compensation may include performance bonuses, equity, and a comprehensive benefits package.

Employ is an Equal Opportunity employer.

Employ is an EVerify employer.