Senior Solutions Architect

Job Title: Solutions architect

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 partnerswith senior engineers, and consulting leads to implement scalable, production-ready systems for HCLTechEnterprise customers.

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

Key Responsibilities

Solution Implementation & Delivery

Build and deploy AI-powered solutions, including LLM-based workflows, copilots, and automation tools inclient 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 andprovider 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 deliverintegrated 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, ensuringsolutions 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 interfacesas 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 ambiguousproblems, developing solution recommendations, and delivering against client or business objectives

Demonstrated experience working in client-facing engagements, including partnering directly withstakeholders to understand needs, communicate solutions, and support delivery in real-worldenvironments

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

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