Forward Deployed Engineer

RudraX Technologies Limited; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

RudraX Technologies Limited is seeking a Forward Deployed Engineer (FDE) to work at the intersection of engineering, product, and customer delivery. This is not a traditional software role; you will engage directly with customers to understand complex business needs, design solutions, and take them into production.

You will own projects end-to-end, from discovery and prototyping to architecture, implementation, deployment and iteration, collaborating with Product, Engineering, AI/ML, and GTM

Job description

We at RudraX are looking for a Forward Deployed Engineer (FDE) to work at the intersection of engineering, product, and customer delivery.

This is not a traditional software engineering role. You will work directly with customers to understand complex business and technical problems, design solutions, build them, and take them into production.

You will own projects end-to-end, from technical discovery and rapid prototyping to architecture, implementation, deployment, and iteration. You will work closely with customer engineering teams while partnering internally with Product, Engineering, AI/ML, and Go-To-Market teams.

The ideal candidate combines strong software engineering fundamentals with the ability to operate in ambiguous environments, communicate with customers, and ship production systems quickly.

What You'll Do:

• Own customer deployments end-to-end: Lead technical discovery, solution design, implementation, testing, deployment, and production rollout.
• Build production software: Design and develop full-stack applications, APIs, integrations, data pipelines, automation systems, and AI-powered workflows.
• Embed with customers: Work directly with customer engineering and business teams to understand workflows, technical environments, constraints, and desired outcomes.
• Turn problems into technical solutions: Translate ambiguous business requirements into clear technical architectures and implementation plans.
• Prototype rapidly: Build proof-of-concepts and MVPs quickly to validate ideas before evolving successful prototypes into scalable production systems.
• Integrate complex systems: Connect our technology with customer APIs, databases, cloud infrastructure, enterprise software, and internal systems.
• Deploy AI systems: Build and productionize applications involving LLMs, AI agents, retrieval systems, automation, and other AI-powered capabilities where relevant.
• Troubleshoot in production: Diagnose integration, infrastructure, application, data, and performance issues and drive them through resolution.
• Drive adoption and impact: Ensure solutions do more than technically work - they must solve the customer's problem and become useful parts of their workflows.
• Bring customer insights back into the product: Identify recurring requirements, technical limitations, and opportunities that should influence the product and engineering roadmap.
• Create reusable solutions: Turn successful customer implementations into reusable components, architectures, tooling, documentation, and engineering best practices.

What We're Looking For

• Strong software engineering fundamentals and experience building production applications.
• Experience building backend services, APIs, integrations, and modern web applications.
• Strong understanding of databases, system architecture, distributed systems, and cloud infrastructure.
• Experience deploying applications using platforms such as AWS, Azure, or GCP.
• Familiarity with containers, CI/CD, observability, and production deployment practices.
• Ability to independently take a technical problem from an ambiguous requirement to a working production solution.
• Strong debugging and problem-solving skills across the application stack.
• Ability to communicate technical concepts clearly to both engineers and non-technical stakeholders.
• Comfortable working directly with customers and taking ownership of technical outcomes.
• Ability to operate effectively in fast-moving environments where requirements can change quickly.

AI/LLM Experience

• Experience building AI applications is highly desirable. This could include:
• LLM APIs and foundation models
• AI agents and tool-calling systems
• Retrieval-Augmented Generation (RAG)
• Vector databases and semantic search
• AI evaluation and observability
• Prompt and context engineering
• AI workflow automation
• Production guardrails and reliability

Nice to Have:

• Previous experience as a Forward Deployed Engineer, Solutions Engineer, Founding Engineer, Solutions Architect, Technical Consultant, or similar customer-facing engineering role.
• Experience with Kubernetes, Docker, Terraform, or infrastructure-as-code.
• Experience designing enterprise integrations and data pipelines.
• Experience working with security-conscious or regulated customers.