Senior AI Engineer
Lever · Bengaluru · onsite · Posted 70d ago
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About this role
Employ is transforming how hiring gets done. With our three ATS solutions - Jobvite, Lever, and JazzHR - plus cutting-edge AI Companions, we free recruiters from admin work and give them more time for what matters: connecting with people. More than 23,000 global customers rely on Employ to make millions of candidate connections each year, helping them hire smarter, faster, and at scale. From growing startups to the world s most recognized brands, we re redefining what s possible in talent acquisition.
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 Foundations 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.
Architect & Ship AI-Native Systems
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Lead the architecture and delivery of end-to-end AI-powered systems, including agents, RAG pipelines, orchestration layers, and reasoning workflows.
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Translate product vision into scalable technical systems.
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Define contracts, state management strategies, and guardrails for AI-driven workflows.
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Own and evolve API contracts that AI systems interact with, ensuring reliability, idempotency, authentication safety, and rate limiting.
Engineer Reliability at Scale
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Design schema enforcement and validation layers for AI-generated outputs.
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Implement retries, fallback strategies, and failure-mode containment.
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Establish evaluation frameworks for benchmarking, regression testing, and drift detection.
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Create observability standards for AI systems, including structured logging, telemetry, tracing, and performance monitoring.
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Productionize experimental AI capabilities into scalable, secure services.
Set Direction & Elevate the Organization
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Establish architectural patterns and standards adopted across teams.
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Mentor engineers in AI-native and spec-driven development practices.
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Influence engineering culture through clarity, urgency, and execution.
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Decompose high-level business outcomes into executable technical systems.
- 4+ years building AI-augmented product capabilities (LLMs, RAG systems, agents, orchestration frameworks).
- Event-Driven & Asynchronous Systems : Experience designing decoupled systems using queues such as Kafka, SQS, or BullMQ, and implementing asynchronous workflows that prevent blocking operations in user-facing systems.
- State Management Strategy : Experience persisting state across sessions, managing context windows efficiently, and handling concurrency and race conditions when multiple agents interact with shared data.
- Structured Data Enforcement : 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.
- API Design & Integration : Strong understanding of REST, GraphQL, or RPC interface design, along with authentication, rate limiting, and idempotent API patterns.
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
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.
If you d like more details about how compensation is determined or how benefits factor in, please get in touch. We re committed to fair, transparent pay and want to make sure you have the information you need.
Disclaimer: This job description has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.
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