Job Summary

The Forward Deployed Engineer (FDE) is a hands-on engineering role focused on building and deploying AI-powered solutions within client environments. Working as part of client-facing delivery teams, this role partners with senior engineers, and consulting leads to implement scalable, production-ready systems for HCLTech Enterprise customers.

FDEs contribute directly to solution delivery-translating defined requirements into working systems, building integrations, and supporting deployments. While primarily focused on engineering execution, the role also operates in client settings, requiring strong collaboration and the ability to support technical discussions with both engineering and business stakeholders.

Key Responsibilities

• Solution Implementation & Delivery
• Build and deploy AI-powered solutions, including LLM-based workflows, copilots, and automation tools in client environments
• Implement integrations between AI models, APIs, and enterprise healthcare systems
• Translate defined solution designs into high-quality, production-ready code
• Contribute to end-to-end delivery by supporting development, testing, and deployment activities
• Hands-on Engineering
• Develop solution components using modern programming languages (e.g., Python, Python API, Java, SQL) and engineering frameworks
• Work with distributed systems and cloud platforms to support scalable, reliable deployments
• Assist with data preparation, prompt configuration, and model integration for AI-driven solutions
• Troubleshoot and resolve technical issues during development and deployment
• Client Delivery Support
• Work alongside senior engineers and consulting leads in client engagements across healthcare payer and provider organizations
• Support technical discussions and working sessions with client stakeholders
• Help execute on defined project plans, timelines, and deliverables
• Contribute to iterative development cycles, incorporating client and team feedback
• Collaboration & Translation
• Partner with cross-functional teams, including engineering, platform, and product teams, to deliver integrated solutions
• Translate technical requirements into actionable development tasks
• Communicate progress, risks, and technical considerations clearly within the team
• Support alignment between technical implementation and client expectations
• Documentation & Knowledge Transfer
• Document solution components, integration points, and deployment processes
• Support knowledge transfer to client technical teams to enable adoption and sustainability
• Contribute to reusable implementation patterns, assets, and playbooks
• Success Measures
• Delivers high-quality solution components that meet performance, reliability, and security expectations
• Contributes effectively to end-to-end client delivery efforts
• Demonstrates strong execution in translating requirements into working systems
• Communicates clearly within teams and supports client delivery activities
• Builds capability in both technical implementation and client engagement over time
• Demonstrates the ability to design and develop prototypes with a clear path to production, ensuring solutions are scalable, supportable, and can be transitioned effectively to production engineering teams

Skill Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field
• Total 15+ year of Experience in Client Facing - AI Implementation Cloud platforms Application interfaces as Solution Architect.
• 5+ years of proficient experience in at least one programming language (e.g., Python, Python APIs, Java, SQL)
• 4+ years of experience operating in a consulting or advisory capacity, including structuring ambiguous problems, developing solution recommendations, and delivering against client or business objectives
• Demonstrated experience working in client-facing engagements, including partnering directly with stakeholders to understand needs, communicate solutions, and support delivery in real-world environments
• Experience working with APIs, data pipelines, or distributed systems
• Familiarity with cloud platforms (e.g., AWS, Azure, or GCP)
• Exposure to AI/ML concepts, including LLMs and prompt engineering
• Demonstrate advanced user capability on CodeX, Claude, etc. and other AI productivity tools
• Ability to work effectively in client-facing delivery environments
• Solid collaboration skills and ability to operate within structured project teams
• Clear communication skills for working with both technical and non-technical stakeholders
• Ability to execute against defined requirements and evolving priorities
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Other Requirements

• Master's degree in a technical discipline (AI/ML, Data Science, Software Engineering)
• Healthcare Domain Expertise; Understanding of healthcare payer and/or provider operations (e.g., claims, utilization management, care delivery, revenue cycle)
• Familiarity with healthcare data considerations (e.g., privacy, compliance) is a plus
• Solid execution focus with attention to detail and code quality
• Ability to work in fast-paced environments with multiple priorities
• Willingness to take ownership of assigned components and deliver reliably
• Continuous learning mindset, particularly in AI and emerging technologies