Solutions Manager

HCL Technologies Limited; Charlotte, Northern (NC, KY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Performance-based bonuses

Medical, dental, vision insurance

401(k) retirement plan

Paid time off

Job summary

HCLTech is seeking a Forward Deployed Engineer embedded with clients to turn ambiguous business problems into working software quickly. You will own outcomes end-to-end, prototype agents, and lead a small team to ship and sustain production-grade solutions using AI/GenAI with Responsible AI and security baked in.

You will build agents with ADKs, Python frameworks, and governance, integrating into client ecosystems with secure APIs, while driving delivery efficiency and measurable ROI across

Qualifications

• Strong Python engineering: idiomatic, typed, tested
• Hands-on agent building with at least one ADK
• Solid command of agent engineering: prompt, context, RAG, MCP
• Eval-driven development: design evals and metrics
• Standards-based integration and DevSecOps
• Conceptualize a business problem as an agent quickly
• Client-facing maturity and ownership of outcomes
• Experience mentoring or leading small teams

Responsibilities

• Conceptualize fast and stand up working agent prototypes
• Build Business Transformation Agents in Python using ADKs
• Own efficiency: drive delivery and operational ROI
• Engineer the agent core: memory, tools, MCP, multi-agent orchestration
• Integrate agents into client ecosystems with secure APIs
• Make reusable components and guardrails for safety
• Prototype and iterate from scaffolding to production-grade code
• Run eval-driven development with test harnesses
• Own AgentOps/DevSecOps: CI/CD, observability, governance
• Lead and mentor a lean team of 3 agent engineers

Skills

Python engineering

Agent building

Eval-driven development

DevSecOps

Client-facing maturity

Mentoring

Tools

Google ADK

LangGraph

CrewAI

OpenAI Agents SDK

AWS Bedrock AgentCore

Semantic Kernel(Microsoft)

Job description

As a Forward Deployed Engineer, you operate at the front line of delivery ; embedded with the client, turning ambiguous business problems into working software, fast. You own the outcome end to end: conceptualize the solution, prototype it, integrate it into the client's real environment, harden it, and lead a small team to ship and sustain it. You are part builder, part consultant, and an engineer who uses AI/GenAI as a force multiplier for delivery and operational efficiency. You bring HCLTech's AI/GenAI capabilities to life inside the client's world, with Responsible AI and security as non-negotiables.

Key Responsibilities

Frameworks: Agent Development Kits (ADKs) ; e.g. Google ADK, LangGraph, CrewAI, OpenAI Agents SDK, AWS Bedrock AgentCore, Microsoft Agent Framework / Semantic Kernel. Framework choice follows the engagement; the discipline is the same.

Models: Multi-LLM via the kit (e.g. Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost.

Interfaces: Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client systems.

What you'll do

• Conceptualize fast: embed with stakeholders, frame a business process as an agentic solution, and stand up a working agent prototype in days, not weeks.
• Build Business Transformation Agents: design and ship single-agent and multi-agent systems in Python using ADKs that automate and transform real client workflows, with measurable ROI.
• Own efficiency as the scorecard: drive delivery efficiency and operational efficiency ; shorter cycle times, less manual effort, higher accuracy, lower cost-to-serve.
• Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG / context-graph retrieval, memory, tool / function calling, MCP integration and multi-agent orchestration.
• Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication.
• Make reusability and predictability the default: build reusable agent components, skills, tool libraries and templates; add guardrails so agent behaviour is predictable, safe and repeatable.
• Prototype and iterate quickly: use the kit's scaffolding to prototype, then harden to production-grade, well-tested Python.
• Run eval-driven development: build evaluation harnesses and test suites that measure agent correctness, safety and regression before anything ships.
• Own AgentOps / DevSecOps: CI/CD for agents, versioning, observability and telemetry, shift-left security, and Responsible AI governance baked in from day one.
• Run a continuous, adaptable feedback loop: feed production telemetry, evals and client feedback back into prompts, context and agent design.
• Stay ahead of the curve: adopt evolving agent frameworks and patterns quickly, and bring field learnings back to the practice.
• Lead and mentor: set technical direction for a lean team of 3 agent engineers, raise the engineering bar, and grow the pod's agentic capability.

What you’ll bring (must-have)

• Strong Python engineering ; idiomatic, typed, tested and packaged code; on a foundation of solid software engineering principles (design, version control, architecture).
• Hands-on agent building with at least one agent development kit (Google ADK, LangGraph, CrewAI, OpenAI Agents SDK, AWS Bedrock AgentCore or Microsoft Agent Framework / Semantic Kernel).
• Solid command of agent engineering: prompt engineering, context engineering, prompt caching, RAG / context graphs, tool / function calling, MCP, and multi-agent orchestration.
• Eval-driven development: designing evaluation harnesses and measuring agent quality, safety and reliability.
• Standards-based integration and DevSecOps: APIs, secure auth, CI/CD, observability and AgentOps.
• Ability to conceptualize a business problem as an agent quickly, and operate effectively in ambiguous, customer-embedded settings.
• Client-facing maturity: translates fluidly between technical and non-technical stakeholders, and owns outcomes.
• Experience mentoring or leading small engineering teams.

What great looks like (strongly preferred)

• Fluency across multiple ADKs and the judgment to pick the right one per engagement.
• Deploying agents to managed runtimes at enterprise scale (e.g. Vertex AI Agent Engine, Bedrock AgentCore) with governance and cost control.
• Domain depth in a transformation area - finance operations, supply chain, HR, claims or compliance.
• Experience with an enterprise agent platform, including Responsible AI and governance at scale.
• A track record of turning agents into reusable accelerators or IP adopted beyond a single engagement.

At HCLTech, you'll supercharge your potential. You'll find your career. And you’ll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026totaled $14.8billion.

Compensation and Benefits

A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies.

In addition, this role is eligible for the following benefits subject to company policies:

• medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance
• employee assistance program
• 401(k) retirement plan
• 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year)
• 10 paid holidays per year