Principal Forward Deployed Engineer

Systems Limited; Punjab; On-site; PKR 400,000 - 800,000; Full time

Job summary

iSystems Ltd seeks an experienced GenAI Delivery Lead to own end-to-end builds onsite with clients, from PoC through production go-live. You will architect, implement, and integrate the GenAI/agentic solution into the client environment.

You will lead the delivery pod, manage client expectations, and collaborate with presales when needed. This role demands hands-on architecture, strong communication, and a proven track record delivering production-grade systems under tight deadlines.

Qualifications

• 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 — Azure AI Foundry, AWS Bedrock/Strands Agents, and Google Vertex AI; comfortable with LangChain, LlamaIndex as open-source options.
• 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

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

Skills

GenAI/LLM/agentic build

Full-stack GenAI stack

Debugging across stack

Enterprise integration (SSO, legacy)

GenAI platforms (Azure Foundry, Bedrod

Tools

LangChain

LlamaIndex

Azure AI Foundry

AWS Bedrock

Vertex AI

OAuth/SSO integration

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