Senior Forward Deployed Engineer

Senior Forward Deployed Engineer

*Client Delivery & AI Engineering*

The Role

We are looking for a Senior Forward Deployed Engineer who can be dropped into a client engagement and trusted to run a workstream end-to-end with minimal oversight. You are an AI-native operator who builds, configures, and extends solutions in live customer environments. You are not a retrained consultant or a business analyst with access to AI tools. The closest analogues to this role in the industry are forward-deployed engineers at Palantir or Scale AI.

As a Senior FDE, you lead with deep expertise in one specialization but operate across the full problem space. You are the person who walks into a client meeting with a vague problem and walks out with a workable scope. You decompose ambiguity, ship working solutions fast, and ensure that what you build is actually adopted — not just deployed.

You are client-ready from day one. You represent IG Labs in every interaction. You mentor Junior FDEs, set the standard for what good looks like, and contribute to IP capture that makes every future engagement faster.

We are hiring across specializations. Your primary depth could be in ML/AI, Data Engineering, Full Stack Development, Analytics/BI, or DevOps — we will match you to engagements based on what the client problem requires.

The T-Shaped Senior FDE

The Horizontal Bar — Senior Level Expectations

At the Senior level, these are not things you can do with support — they are things you do independently, instinctively, and at a standard that others can learn from:

• Lead client conversations: run discovery sessions, present solutions, navigate pushback, and build trust through technical credibility
• Decompose ambiguous problems into buildable scope: you do not wait for requirements — you create them
• Ship production-quality code that an offshore engineer in a different timezone can pick up and extend without calling you
• Work across the stack without hesitation: your specialization determines where you lead, not where you stop
• Self-manage completely: create your own task breakdowns, set timelines, flag risks before anyone asks
• Document as a reflex, not a chore: architecture decisions, runbooks, and handoff notes produced as you work
• Contribute to IP capture actively: work with the TA to identify reusable patterns and ensure Factory backlog items are logged
• Own customer adoption: watch for adoption signals, iterate based on real user feedback
• Support sales and pre-sales: join prospect conversations, shape engagement scope, provide defensible estimates
• Mentor Junior FDEs: elevate the team through code review, pairing, and coaching

The Vertical Bar — Your Depth

You lead with deep expertise in one specialization. At the Senior level, you make architectural recommendations in your domain that the Technical Architect trusts without heavy review.

Specialization

Focus Area

Machine Learning / AI

Model development, LLM orchestration, agentic workflows, MLOps, evaluation and fine-tuning

Data Engineering / ETL

Pipelines, ingestion, transformation, data quality, warehousing, ontology design

Full Stack Development

Applications, APIs, frontend, backend, agent UIs, end-to-end feature delivery

Analytics / BI

Reporting, visualization, insight generation, metric design, decision support

Infrastructure / DevOps

Cloud architecture, CI/CD, environments, reliability, deployment automation

Key Responsibilities

Client-Facing Delivery

• Own one or more workstreams within a client engagement end-to-end — from discovery through build, deployment, and adoption
• Build and configure agent workflows, data pipelines, integrations, and AI-powered solutions in live customer environments
• Operate as the technical authority on your workstream
• Partner with the Technical Architect on cross-cutting architectural decisions
• Iterate rapidly based on client feedback — ship working solutions fast, validate with real users, and refine

IP Capture & Platform Contribution

• Identify reusable patterns, components, and frameworks within your workstream and flag them for abstraction
• Work with the Technical Architect to contribute production-grade assets to the IP library
• Ensure every engagement you work on produces Factory backlog items — this is non-negotiable
• Draw on existing IP library assets to accelerate delivery — reuse is as important as creation

Team & Practice Development

• Mentor Junior FDEs through code review, pairing sessions, and real-time coaching on client engagements
• Set the quality bar for code, documentation, and client communication within your POD
• Contribute to internal knowledge sharing — write-ups, tech talks, and lessons learned
• Help assess and interview FDE candidates as the team scales

Pre-Sales & Engagement Shaping

• Join prospect conversations to demonstrate technical credibility and help shape what we commit to
• Contribute to SOWs, proposals, and scoping conversations with defensible technical estimates
• Evaluate incoming opportunities for technical feasibility and team fit

Qualifications

Required

Strongly Preferred

5+ years of hands-on software engineering experience with a track record of shipping production systems

Deep expertise in at least one specialization area: ML/AI, Data Engineering, Full Stack, Analytics/BI, or DevOps

Demonstrated ability to work directly with clients or external stakeholders

Experience operating in ambiguous environments — consulting, professional services, startups

Strong fluency with AI tools and workflows

Proven ability to work across the stack when needed

Strong written and verbal communication

Experience mentoring junior engineers

Experience building agentic AI systems, RAG architectures, or LLM orchestration workflows

Background in professional services, systems integration, or technology consulting

Experience with distributed or offshore delivery teams

Familiarity with MCP (Model Context Protocol)

Prior experience contributing to an IP library or accelerator repository

Experience in regulated industries: financial services, healthcare, or insurance

Familiarity with cloud platforms (AWS, Azure, GCP)

Core Competencies

Technical Depth

Client Partnership

Problem Decomposition

IP Mindset

Self-Management

Mentorship

Communication Clarity

Delivery Accountability