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Forward Deployed Engineer (Fde)
Posted on Sept. 28, 2026
- Ka, India
- 0 - 0 USD (yearly)
- Full Time
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Job Information
- Date Opened 09/15/2026
- Job Type Full time
- Industry Technology
- State/Province Karnataka
- Zip/Postal Code 560048
- City Banglore
- Country India
About Us
At Innover, we endeavor to see our clients become connected, insight-driven businesses. Our integrated Digital Experiences, Data & Insights and Digital Operations studios help clients embrace digital transformation and drive unique outstanding experiences that apply to the entire customer lifecycle. Our connected studios work in tandem to reimagine the convergence of innovation, technology, people, and business agility to deliver impressive returns on investments. We help organizations capitalize on current trends and game-changing technologies molding them into future-ready enterprises.
Take a look at how each of our studios represents deep pockets of expertise and delivers on the promise of data-driven, connected enterprises.
Experience Required
12+ years of experience
Job Description
A Forward Deployed Engineer is the sharp end of Innover's delivery. You embed directly with an enterprise client, sit close to their product and technology leadership, and turn ambiguous business problems into working, production-grade software fast. You own outcomes rather than tickets: architecture through build, test, deployment, and production support.
What sets this role apart is how you build. Our FDEs are fluent, daily practitioners of AI-native engineering — using agentic coding tools and disciplined guardrails to compress delivery timelines without sacrificing quality. You are the forward point that connects the client to Innover's broader delivery pods, translating in both directions so the right thing gets built and shipped.
What you'll do
Embed with the client. Work alongside the client's engineering, product, and executive teams; understand their domain, their systems, and their constraints; and become a trusted technical partner.
Own the full lifecycle. Take features from architecture and design through implementation, testing, deployment, and production support — shipping into the client's environment.
Build AI-native. Use Claude Code, Cursor, and agentic workflows as core tools in daily development; design the conventions and guardrails that keep an AI-augmented codebase fast, maintainable, and safe.
Translate business into software. Convert business requirements into technical solutions, scope and de-risk delivery under ambiguity, and communicate progress, risk, and tradeoffs to non-technical and executive stakeholders.
Set the standard. Define architecture patterns and code-quality standards on the engagement, review designs, and mentor engineers — including Innover's delivery pods that support the account.
Bridge to delivery. Connect the client to the wider Innover team, decomposing work into clear, reusable, API-driven modules that pods can build against.
What you'll bring
Engineering foundation
12+ years designing and shipping scalable SaaS / B2B platforms end to end, with a track record of owning technical direction.
Deep, hands-on expertise across the stack: Node.js, React / Next.js, TypeScript, and Python.
Cloud-native delivery on AWS (Lambda, ECS/EC2, S3, RDS, API Gateway), with Docker, Kubernetes, and CI/CD.
Strong data and architecture chops: PostgreSQL, DynamoDB, Redis/SQL; microservices, event-driven and distributed systems, multi-tenant design.
Full SDLC ownership — architecture, build, test, deploy, and production support — not just feature work.
AI-native engineering (non-negotiable)
This is the differentiator. We want engineers who genuinely build this way today, not who list the tools:
Daily production use of agentic coding tools (Claude Code, Cursor, and similar) as core to the workflow.
Experience authoring project conventions and guardrails (e.g. CLAUDE.md, structured prompts) that curb LLM failure modes — hallucinated APIs, type-system bypasses, scope creep.
AI-augmented CI/CD: automated code review, test generation, and security analysis — with a habit of measuring the effect on speed and defect rates before scaling adoption.
Judgment on tooling: matching models to task type on cost and capability, and coaching engineers of varying AI fluency. RAG / agentic patterns are a plus.
Client-facing strength
Comfortable partnering directly with CTOs, product leaders, and executives; can hold the room and earn trust.
Proven ability to operate under ambiguity and drive to an outcome without a fully-specified brief.
Based in the US and authorized to work in the US.
Nice to have
Domain depth in a client vertical (e.g. financial services, real estate, manufacturing, logistics).
Architecture-review or design-standards leadership at scale (e.g. chairing an Architecture Review Board).
Serverless-first design, observability (Datadog, CloudWatch, OpenTelemetry), Terraform/IaC, and security fluency (OAuth2/OIDC, SOC 2, RLS, KMS/IAM).
Patents, open-source, or shipped side projects that show you build with these tools for real.
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