Agentic AI - Forward Deployed Engineer

Job description

🚀 HCLTech is Hiring | Agentic Forward Deployed Engineer (FDE) - AI Are you passionate about building cutting-edge AI agents and transforming business processes through Agentic AI? Join HCLTech and be part of the next wave of enterprise AI innovation. 📍 Location: PAN India 💼 Experience: 10+ Years ✅ Mandatory Application Link: To be considered for this opportunity, please apply using the link below: 🔗 https://forms.cloud.microsoft/r/eWzCLrJ1Gk About the Role As an Agentic Forward Deployed Engineer (FDE) , you will work directly with clients to transform complex business challenges into production-ready AI agents. You will design, build, deploy, and optimize autonomous and multi-agent systems that drive measurable business outcomes across functions such as procurement, finance, compliance, onboarding, claims management, and more. Key Skills & Technologies Programming: Python (Mandatory) Agentic AI Frameworks: • Google ADK • LangGraph • CrewAI • OpenAI Agents SDK • AWS Bedrock AgentCore • Microsoft Agent Framework • Semantic Kernel • Other Agent Development Kits (ADKs) LLM Platforms: • Azure OpenAI • Claude on AWS Bedrock • Gemini Core Expertise: • Agentic AI • Multi-Agent Architectures • RAG (Retrieval-Augmented Generation) • Prompt Engineering • Context Engineering • MCP (Model Context Protocol) • AI Evaluation Frameworks • AgentOps & DevSecOps What You'll Do ✔ Design and deploy Business Transformation Agents with measurable ROI ✔ Build autonomous and multi-agent systems for real-world enterprise workflows ✔ Integrate AI agents with enterprise applications using secure APIs ✔ Implement RAG, memory, tool calling, MCP integration, and agent orchestration ✔ Drive AgentOps practices, governance, observability, CI/CD, and security ✔ Develop reusable agent frameworks, templates, and guardrails ✔ Collaborate with business and technology stakeholders to deliver scalable AI solutions ✔ Stay ahead of emerging AI and Agentic technologies Key Responsibilities • Assess enterprise IT landscapes and identify transformation opportunities. • Define solution architectures across business, application, infrastructure, and operations layers. • Lead architecture discussions with business and technology stakeholders. • Drive innovation through emerging AI technologies and best practices. • Contribute to technical assets, whitepapers, and knowledge repositories. • Mentor teams and ensure Responsible AI, security, and governance standards are embedded into every solution.