Forward Deployed Engineer Hybrid / Full time Ahmedabad, India

Attri Inc.; Hinoba-an; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Attri Inc. is seeking an experienced AI software engineer to own client engagements from discovery to delivery, building production systems with agent workflows, data pipelines, and full-stack services. You will integrate AI solutions into clients’ stacks and ensure reliable production operations across time zones.

You will work hands-on with LLMs, RAG, and prompt engineering, delivering value while communicating clearly with senior stakeholders and maintaining ownership of outcomes.

Qualifications

• 3–5 years building and shipping production software.
• Solid data chops: SQL and data pipelines across REST/GraphQL APIs.
• Cloud fluency: AWS/GCP/Azure, containers, CI/CD, infra sense for client deployments.
• Hands-on with LLMs, RAG, agent orchestration, and prompt engineering.
• Strong client-facing communication in English with senior stakeholders.
• Willingness to work across time zones and async collaboration.

Responsibilities

• Own accounts end-to-end. Lead discovery with client stakeholders and translate business problems into technical solutions and delivery plans.
• Build production systems: agent workflows, data pipelines, backend services, RAG systems, and full-stack apps creating measurable value.
• Integrate into client stacks: CRMs, ERPs, databases, internal APIs, auth, and legacy systems.
• Own deployment reliability: diagnose and fix production issues, often with the client in the room.
• Move fast with AI: use AI coding tools and agent workflows to accelerate delivery.
• Close the product loop: identify patterns across deployments and feed insights back to the core product team.

Skills

End-to-end ownership

Client engagement

Production systems

AI frameworks

Data pipelines

Tools

AWS

GCP

Azure

REST/GraphQL

Containers

Job description

Attri is AI consulting and engineering for regulated teams. We take clients from ROI-ranked strategy to custom agents deployed in production, governed end-to-end by Enterprise OS — a managed governance service built on five control pillars: Identity & Access, Data Lifecycle, Evidentiary Record, Pre-Prompt Governance, and Intelligence & Continuous Assurance. We work with legal, healthcare and financial services teams who have to prove their AI is safe to run — self-hosted, VPC or on-prem, with SOC 2 Type II and HIPAA + BAA.

Responsibilities

• Own accounts end-to-end. Lead discovery directly with client stakeholders — from ops analysts to VPs and CTOs — and translate ambiguous business problems into a concrete technical solution and delivery plan. No layer of PMs or solution architects between you and the customer.
• Build the thing. Design, build, and ship production systems: agent workflows using latest AI frameworks, custom data pipelines, backend services, RAG systems, document/voice automation, and full-stack apps that create measurable value.
• Integrate into the real world. Wire agents into the client's existing stack — CRMs, ERPs, databases, internal APIs, auth (SSO/SAML/OAuth), and legacy systems that were never meant to talk to anything.
• Own reliability. When a deployment breaks in production, you diagnose and fix it — often live, with the client's team in the room. You own the outcome, not just the code.
• Move fast with AI. Use AI coding tools and agentic workflows as a daily force multiplier — you should be shipping more, faster, because you use these tools well.
• Close the product loop. Spot patterns across deployments, turn one-off solutions into reusable building blocks, and feed field insight back to the core product team so the platform improves with every engagement.

Requirements

• 3–5 years building and shipping production software, with a track record of owning systems end-to-end — not just features.
• Solid data chops. Confident with SQL and building/operating data pipelines and integrations across REST/GraphQL APIs.
• Cloud & deployment fluency. AWS/GCP/Azure, containers, CI/CD, and enough infra sense to stand up and debug a client deployment yourself.
• Modern AI fluency. Hands-on with LLMs, RAG, agent orchestration, and prompt engineering — you've built with these, not just read about them.
• The “army of one” temperament. You can run a client meeting, scope the work, build it, and support it — and you're energized by owning that whole arc.
• Client-facing communication in English. You can hold your own in a room with senior stakeholders, run discovery, and explain technical trade-offs to non-technical people with low ego. You listen well and translate even better.
• Comfort across time zones. Many of our clients are global (incl. US); you're okay with occasional overlap hours and async collaboration.
• Radical ownership and comfort with ambiguity. You default to figuring it out. Undefined problems and shifting requirements are the job, not the exception.

Great to have

• Prior client-facing / consulting / solutions / forward-deployed experience.
• Enterprise integration experience (SSO, security reviews, compliance-sensitive environments).
• Domain exposure in document processing, workflow automation, or any AI-first use cases.
• Startup or 0→1 experience — you've been the person who makes things exist.