Lead Assistant Manager

Location:

Level:

About EXL Service

AI into enterprise operations

MiAI Call Simulator, AI Trainer, Upskill.AI, and Transition AI Toolkit

Insurance, Healthcare, Banking, and Retail

AI Engineers with strong full-stack development skills

Advanced Agentic AI systems

next-generation AI-driven automation

Key Responsibilities

• AI Engineering & Development
• Design, develop, and deploy Agentic AI workflows using LLMs, orchestration frameworks (LangGraph, LangChain, Semantic Kernel), and advanced prompting strategies.
• Build scalable full-stack applications integrating AI agents with enterprise platforms (ServiceNow, Salesforce, Jira, custom APIs).
• Develop self-healing automations, API connectors, and middleware to enable seamless human-AI collaboration.
• Architecture & Systems Integration
• Architect end-to-end AI solutions covering data ingestion, model orchestration, microservices, and UI layers.
• Leverage cloud-native infrastructure (Azure OpenAI, AWS Bedrock, GCP Vertex AI) to build secure and compliant AI systems.
• Ensure AI agents adhere to governance, auditability, and compliance frameworks (GDPR, HIPAA, PCI-DSS).
• Product & Innovation
• Collaborate with Product Managers to translate business requirements into AI-first features.
• Prototype, test, and optimize Agentic AI capabilities for enterprise-scale adoption.
• Contribute to EXL’s AI Innovation labs with cutting-edge solutions in conversational AI, simulation, and process automation.
• Team & Delivery
• Mentor junior engineers in AI frameworks and full-stack practices.
• Drive Agile ceremonies, ensure backlog delivery, and maintain production-ready AI deployments.
• Partner with cross-functional teams (SMEs, designers, DevOps, QA) to ensure quality and scalability.

Required Skills & Experience

• Core AI/ML Skills
• 5–8 years of experience in software engineering / AI engineering.
• Strong experience in building Agentic AI solutions with LLM orchestration (LangChain, LangGraph, AutoGen, Semantic Kernel).
• Hands-on with RAG (Retrieval Augmented Generation), fine-tuning, and multi-agent orchestration.
• Exposure to voice / conversational AI (Azure Cognitive Services, Twilio, Dialogflow, etc.) a plus.
• Full-Stack Development
• Strong in JavaScript/TypeScript, React/Next.js, Node.js, Python.
• Proficiency in REST / GraphQL APIs, microservices, containerization (Docker, Kubernetes).
• Strong knowledge of databases (SQL/NoSQL, vector DBs like Pinecone, Weaviate, Chroma).
• Cloud & DevOps
• Experience with Azure (preferred), AWS, or GCP AI services.
• Knowledge of CI/CD, MLOps pipelines, and monitoring tools.
• Familiarity with security practices (OAuth2.0, JWT, API security, data encryption).
• Soft Skills
• Strong problem-solving with system-level thinking.
• Ability to work in agile squads and deliver in fast-paced environments.
• Good communication and ability to collaborate with product/business teams.

Preferred / Good-to-Have

• Exposure to Agent simulation environments for training and testing (e.g., CrewAI, OpenAI Swarm).
• Experience with GenAI integrations in enterprise L&D, Customer Service, or Operations platforms.
• Contributions to open-source AI frameworks.
• Certifications: Azure AI Engineer Associate, TensorFlow Developer, or equivalent.