Principal Forward Deployed Engineer - Gen AI

Systems Limited; Punjab; On-site; PKR 4,000,000 - 8,000,000; Full time

Job summary

iSystems Ltd. seeks an experienced GenAI delivery lead to embed on-site with clients and drive end-to-end GenAI/agentic solutions from PoC to production go-live. You will own architecture, integration, and production readiness while coordinating a delivery pod and cross-functional teams.

Responsibilities include on-site adaptation, debugging in client environments, and setting up monitoring and handoff docs for the client. Prior enterprise integration and strong communication are essential.

Qualifications

• 10–15+ yrs shipping production software with hands-on GenAI/LLM/agentic build experience.
• Full‑stack range across GenAI application layer orchestration, retrieval, integration, deployment.
• Comfortable debugging across stack: infra, application code, model behavior.
• Experience integrating with enterprise systems (SSO, legacy APIs, data governance constraints).
• Knowledge of major agentic/GenAI platforms (Azure AI Foundry, AWS Bedrock/Strands, Vertex AI) and open‑source options (LangChain, LlamaIndex).
• Strong client-facing communication and ability to explain tradeoffs under time pressure.

Responsibilities

• Own end-to-end build of GenAI/agentic solution from scoped architecture through implementation.
• Integrate solution into client's live environment (auth, data access, legacy interfaces).
• Adapt build on-site as edge cases surface during real usage.
• Debug and resolve production issues directly within the client's infrastructure.
• Set up monitoring and handoff documentation for the client's team.
• Serve as the primary technical contact for the client during delivery.
• Head the delivery pod for GenAI engagements when appropriate.
• Support presales when pursuit volume exceeds hub capacity.
• Feed learnings back into estimation and pattern library.

Skills

GenAI/LLM builds

End-to-end delivery

Full-stack orchestration

Client-facing communication

On-site delivery

Problem solving under deadlines

Tools

Azure AI Foundry

AWS Bedrock

Vertex AI

LangChain

LlamaIndex

Job description

Embeds on-site with the client to build and ship the GenAI/agentic solution end-to-end from PoC through production go-live.

KEY RESPONSIBILITIES

• Own end-to-end build of the GenAI/agentic solution once scoped architecture through implementation
• Integrate the solution into the client's live environment auth, data access, existing systems, legacy interfaces
• Adapt the build on-site as real usage surfaces edge cases the original design didn't anticipate
• Debug and resolve production issues directly within the client's infrastructure
• Set up monitoring and handoff documentation for the client's own team
• Serve as the primary technical point of contact for the client during delivery
• Head the delivery pod for GenAI/agentic engagements when appropriate
• Flex into presales support when pursuit volume outpaces Hub capacity
• Feed build learnings back into the practice's estimation and pattern library
• Manage client expectations under shifting scope or timeline pressure

REQUIREMENTS & SKILLS

• 10–15+ yrs shipping production software, with hands‑on GenAI/LLM/agentic build experience
• Full‑stack range across the GenAI application layer orchestration, retrieval, integration, deployment
• Comfortable debugging across the stack: infra, application code, model behavior
• Experience integrating with enterprise systems (SSO, legacy APIs, data governance constraints)
• Working knowledge of major agentic/GenAI platforms likely in the client's environment — Microsoft Azure AI Foundry, AWS Bedrock/Strands Agents, and Google Vertex AI; comfortable with open‑source alternatives (LangChain, LlamaIndex) as a good‑to‑have when the client has no platform preference
• Comfortable being the senior technical presence in the room with a client's engineering team
• Strong client‑facing communication explains technical tradeoffs under time pressure
• Track record of taking ambiguous, partially specified designs to a working production system
• Resilient under the pressure of on‑site, client‑facing delivery with visible deadlines
• Prior forward‑deployed, startup, or embedded‑consulting experience is a strong plus