Forward Deployed Engineer

Job OverviewWe 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.ResponsibilitiesLead 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 the scope.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 else.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.Domain ExpertiseAI/Model development, LLM orchestration, agentic workflows, MLOps, evaluation and fine‑tuning.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, dashboards, data storytelling.Infrastructure / DevOps – cloud platforms, CI/CD, observability.Platform ContributionIdentify reusable patterns, components, and frameworks within your workstream and flag them for abstraction.Work with the TA 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 create.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.Join prospect conversations to demonstrate technical credibility and shape commitments.Contribute to SOWs, proposals, and scoping conversations with defensible technical estimates.Evaluate incoming opportunities for technical feasibility and team fit.Qualifications5+ 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 skills.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 repositories.Experience in regulated industries: financial services, healthcare, or insurance.Familiarity with cloud platforms (AWS, Azure, …).#J-18808-Ljbffr