Forward Deployed Engineer- Insurance Domain

Inviting applications for the role of Forward Deployed Engineer- Insurance - Life 3

About the Role

Genpact is looking for a Forward Deployed Engineer (FDE) to sit at the intersection of client operations, engineering, and AI product delivery for our Insurance and Financial Services portfolio. This is a hands-on, embedded engineering role you will work directly inside client environments (or client-facing pods) to rapidly design, build, and iterate on agentic AI, automation, and data solutions that solve real operational problems: claims processing, underwriting workbenches, policy servicing, cash application, submission intake, and back-office transformation.

Unlike a traditional delivery or pre-sales role, the FDE is expected to write code, configure platforms, and ship working solutions in close partnership with client business and IT stakeholders — compressing the gap between problem discovery and production deployment.

What You'll Do

• Embed directly with client teams (Insurance carriers, TPAs, FinServ operations) to understand workflows, pain points, and data landscapes firsthand — not through requirements documents alone.

• Rapidly prototype and productionize AI-enabled solutions: agentic workflows, LLM-based extraction/classification, RPA + AI hybrid automations, and API-first integrations.

• Own the full build lifecycle — from architecture and proof-of-concept through UAT, hypercare, and steady-state handover — often with minimal dedicated engineering support.

• Translate ambiguous business asks (e.g., "reduce submission turnaround time," "automate cash application matching") into scoped technical designs and working prototypes within days, not months.

• Integrate with core insurance/FinServ systems — policy admin systems, claims platforms, document management, CRM (Salesforce), and legacy mainframe/ODS environments.

• Partner with Solution Architects, Automation Architects, and AI Architects to ensure builds align to enterprise patterns (event-driven architecture, canonical data models, API-first integration).

• Instrument solutions for measurable outcomes: FTE release, STP rate, FPY, cycle time reduction, and defect/UAT pass-rate tracking.

• Act as the technical credibility layer in CXO/client governance forums — able to demo live builds, defend architecture choices, and respond to technical objections in real time.

• Drive from pilot to scale: once a build proves value with one client/process, generalize it into a reusable asset or platform capability.

• Provide technical inputs into RFP/proposal responses and BaFO (Best and Final Offer) stages when needed.

What We're Looking For

Experience & Domain

• 10–15 years in software/solutions engineering, with at least 5–7 years working directly in Insurance (P&C, Life, Group Benefits) and/or Financial Services operations or technology.

• Demonstrated experience deploying solutions into live client environments — not just internal R&D or lab settings.

• Working knowledge of insurance domain processes: underwriting, claims, policy servicing, submissions, cash/reconciliation, or loss run processing.

Technical Skills

• Strong hands-on coding ability (Python and/or JavaScript/TypeScript; SQL fluency mandatory).

• Practical experience building with LLMs/agentic frameworks (LangChain, LangGraph, CrewAI, Semantic Kernel, or equivalent) and RAG architectures.

• Experience with RPA and intelligent automation platforms (UiPath, Automation Anywhere, Power Automate) and where to use automation vs. AI vs. workflow engines.

• API integration and iPaaS experience (MuleSoft or equivalent); understanding of event-driven architecture and Canonical Data Models.

• Familiarity with cloud platforms (AWS/Azure/GCP) and standard MLOps/LLMOps practices for deploying and monitoring models in production.

• Comfortable working with legacy and modern data layers alike — mainframe extracts, ODS, CDC pipelines, and modern data warehouses.

Ways of Working

• Bias for building over documenting — comfortable operating with incomplete specs and iterating live with client stakeholders.

• Able to context-switch between deep technical work and CXO-facing conversations in the same day.

• Strong ownership mindset: will independently drive a build from whiteboard to production without waiting for a formal handoff.

• Experience operating in a multi-client, multi-workstream delivery environment, balancing competing priorities and governance cadences (QBRs, UAT tracking, RAG status reporting).

Nice to Have

• Prior experience in a professional services, systems integrator, or BPO transformation environment.

• Exposure to change management frameworks (Prosci ADKAR, Kotter) for driving adoption of AI/automation solutions.

• Prior forward-deployed, solutions engineering, or field engineering title at a product or AI company.

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Education

• Bachelor's degree in Computer Science, Engineering, or related field required; advanced degree a plus.