AI Engineer

Job Summary

Team: Engineering | Location: Chennai / Remote | Manager: SVP of Engineering | Shift: IST | Employment Type: Full Time

We are looking for a Senior AI Engineer to design and build the foundational AI powering the next generation of Experience.com. This is a hands-on architecture and engineering role. You will own the core AI platform, including agent orchestration, tool execution, authorization, durable workflows, evaluation, and observability, working closely with Engineering, Product, Data Science, DevOps, and Security teams.

Responsibilities

• AI Platform Agentic Architecture: Design and build the core platform for AI agents, skills, orchestration, and agentic applications.

• Build reusable capabilities for state management, task routing, tool execution, workflow orchestration, and recovery.

• Define architecture standards for how AI agents securely interact with Experience.com services and enterprise systems.

• Platform Security Reliability: Design authentication, authorization, RBAC, policy enforcement, and multi-tenant isolation for AI agents and their capabilities.

• Build reliable execution with durable workflows, retries, failure recovery, approvals, auditability, and observability.

• Establish evaluation and monitoring practices to ensure AI systems are reliable, secure, and production-ready.

• AI Integrations Platform Engineering: Build secure integrations between agents, MCP/tools, APIs, skills, and domain capabilities.

• Develop scalable, cloud-native and event-driven platform services using Python, APIs, Kafka, Kubernetes, and AWS/GCP.

• Integrate AI capabilities with Experience.coms existing services, data platforms, and infrastructure.

• Technical Leadership: Own the architecture and hands-on implementation of major AI platform initiatives.

• Partner with the Senior Solution Architect to define how the AI platform integrates with core XMP services.

• Establish reusable engineering standards and mentor engineers building AI capabilities.

• Evaluate emerging AI technologies and drive their practical adoption across the platform.

  Requirements

• Engineering Experience: 8+ years of software engineering experience building production systems.

• Strong experience designing and building distributed, cloud-based systems and microservices on AWS and/or GCP.

• Experience with event-driven architectures and technologies such as Kafka.

• Strong proficiency in Python, building production-grade APIs and backend services.

• AI / Agentic Systems Experience: 3+ years building production AI/ML systems, including at least 2 years shipping LLM-based or agentic systems to production.

• Hands-on experience building AI agents and stateful, multi-step agentic workflows using orchestration frameworks.

• Hands-on experience building AI agents and agentic workflows.

• Experience with tool calling and function calling.

• Experience with MCP or equivalent tool integration protocols.

• Experience with RAG, embeddings, vector search, or knowledge-based AI systems.

• Experience with LLM evaluation and AI observability.

• Experience managing LLM cost and latency, including token budgets, caching, and model selection trade-offs.

• Platform Security Experience: Strong understanding or hands-on experience with: Authentication and authorization (OAuth / JWT) Multi-tenant isolation Audit logging Securing agentic systems against prompt injection, excessive tool permissions, and sensitive-data leakage Securing agentic systems against prompt injection, excessive tool permissions, and leakage of PII or customer data

• Architecture Experience designing and documenting large-scale system architectures.

• Strong understanding of distributed systems and cloud architecture.

• Ability to define clear boundaries between AI agents, platform services, domain capabilities, and authoritative business logic.

• Ability to design systems that remain deterministic and secure around inherently probabilistic AI components.

• Experience making architecture and technology decisions based on scalability, reliability, security, and business requirements.

• Good to Have: Experience with Temporal, LangGraph, LangChain, OpenAI Agents SDK, Google ADK, Semantic Kernel, or equivalent orchestration frameworks.

• Experience building MCP servers and clients.

• Experience with graph databases such as Neo4j.

• Experience with Elasticsearch/OpenSearch, Redis, and BigQuery or similar large-scale data platforms.

• Experience working with financial, healthcare, or other security-sensitive systems.

• Experience with Docker and Kubernetes.

• Experience with distributed tracing OpenTelemetry, circuit breakers, and model routing/fallback strategies.

  Skills

• Python

• AWS

• GCP

• Kafka

• Kubernetes

• LLM-based AI agents

• Tool calling / function calling

• Embeddings and vector search

• MCP integration protocols

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.