Forward Deployed Engineer

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Forward Deployed Engineer (AI Solutions)

About Cogentiq (Fractal’s Agentic AI Platform): Cogentiq is Fractal’s secure, scalable, enterprise agentic AI platform that enables teams to build, test, deploy, monitor agents and multi‑agent workflows with strong observability, evaluation, guardrails and RBAC across any cloud or LLM framework. It includes a no/low‑code development console, Agent & MCP Gateways, and an enterprise marketplace for reusable agents, tools, connections and guardrails.

Role Summary: As a Forward Deployed Engineer, You are the engineer on the front line of customer value. You’ll embed directly with strategic customers, understand their real business problems and turn our platform and products into production systems that move the needle on customer outcomes.

You’ll spend most of your time writing and shipping production code in customer environments, integrating systems, building AI/ML-powered workflows and deploying and supporting production deployments end-to-end until they’re stable, adopted and delivering measurable outcomes.

This is an engineering-first role with deep customer exposure: You’ll work closely with senior stakeholders from business and technical teams on the customer side, travel on-site when it makes sense and act as their trusted technical partner. Success is measured in value delivered, user adoption, and accumulation of platform and product leverage.

Key Responsibilities:

• Own the technical success of deployments for a portfolio of strategic customers – from discovery and design through go-live and scale-out.
• Translate ambiguous customer goals (“reduce manual review time”, “improve CS efficiency”, “cut claim processing costs”) into concrete technical roadmaps and implementation plans leveraging and extending our platform and products.
• Define and track deployment KPIs (latency, accuracy, throughput, adoption, business impact) and continuously tune systems to hit them.

• Design and implement full-stack solutions: backend services, data pipelines, integrations and customer-facing assistants and workflows.
• Build and harden production AI systems - including LLM- and agent-based workflows, knowledge pipelines and domain-specific orchestration.
• Integrate with customer infrastructure (APIs, data warehouses, identity, CRM/ERP, internal services) across one or more major clouds.

• Own deployment lifecycles: proofs-of-value, pilots, phased rollouts and post-go-live stabilization.
• Debug gnarly production issues in unfamiliar environments, often under tight time pressure and drive them to root cause and fix.
• Establish monitoring, observability and runbooks so customers can operate solutions with confidence.

• Work side-by-side with customer engineers – pairing on code, reviewing designs and guiding architecture decisions.
• Communicate trade-offs clearly to non-technical stakeholders and help them make informed decisions without drowning them in jargon.
• Influence customer teams to adopt best practices for AI, data and software delivery - even when it means challenging their current approach.

• Bring structured feedback from the field back into our product and engineering roadmap: common integration patterns, missing features, recurring edge cases and opportunities to productize bespoke work.
• Help shape our forward deployed playbook: reusable templates, reference architectures, example repos and internal tooling that make future deployments faster and more repeatable.

What You Bring:

• 3 - 10 years of professional software engineering experience building and operating production systems.
• Strong coding skills in Python plus experience with TypeScript/JavaScript or another modern language; comfortable working full-stack when needed.
• Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure), and with containers/orchestration (Docker, Kubernetes or equivalent).
• Practical experience with modern AI/LLM tooling: building agentic workflows, RAG pipelines, or integrating LLMs into real products.
• Comfortable reading other people’s codebases quickly and making safe changes in unfamiliar environments.

• Proven track record working directly with customers or stakeholders to deliver complex technical projects (consulting, implementation, solutions/field engineering, or similar).
• Excellent communication skills - you can explain technical constraints and risks to a VP in plain language without oversimplifying.
• High ownership and collaboration mindset even while owning your informed opinions

• Bias to action: you’re comfortable moving from rough requirements to working prototypes quickly, then iterating in front of real users.
• Ability to operate in ambiguous, changing environments – switching between customers, industries, and tech stacks without losing momentum.
• Willingness to travel periodically to embed on-site with key customers when it materially accelerates deployment success.

• Experience deploying systems in regulated or complex industries (financial services, government/defence, healthcare, insurance, energy, etc.).
• Background in startups or growth-stage companies where every deployment materially influenced product direction.

Ideal Candidate Profile:

Location Preference: Bengaluru/Mumbai/Gurugram/Pune/Noida/Chennai

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