Forward Deployed Software Engineer

The opportunity

We are seeking a Senior for Forward Deployed Engineer (FDE) with 6+ years of deep, hands-on engineering experience to design, build, and deploy AI-powered solutions directly with clients. This role is ideal for an elite individual contributor who thrives in ambiguous environments, prefers building real systems over managing teams, and can translate business problems into production-grade AI solutions. The individual should have worked on GenAI, AI/ML, Data Science solutions on multiple proprietary enterprise AI tech stacks along with Hyperscalers, Platform AI tech stack.

Role Purpose:

• Lead complex end-to-end deployments in production at strategic customers.
• Lead the discovery, design, development, and deployment of high-impact AI / GenAI-powered solutions in close collaboration with client stakeholders.
• Build LLM-driven applications, RAG systems, and agentic workflows that demonstrate measurable business value.
• Drive innovation by creating reusable accelerators, frameworks, and reference implementations for enterprise GenAI deployments.
• Enable rapid experimentation and large-scale adoption of AI, data, and cloud platforms through hands-on engineering leadership.

Key Responsibilities

• Partner with client business and engineering teams to translate complex problems into executable GenAI solutions.
• Own solution delivery endtoend, from discovery and architecture through production deployment.
• Act as a trusted technical advisor to senior and executive client stakeholders.
• Design and build LLMpowered applications, including copilots, assistants, RAG systems, and agentic workflows.
• Integrate GenAI solutions with enterprise data platforms, APIs, and external systems.
• Optimize solutions across latency, cost, accuracy, scalability, security, and compliance.
• Convert PoCs into productiongrade, enterpriseready platforms through rapid iteration and feedback.
• Architect scalable, reliable, and observable systems using cloudnative patterns.
• Develop reusable accelerators, reference architectures, and best practices for enterprise GenAI adoption.
• Codify best practices for enterprise GenAI deployments.
• Collaborate with internal teams to transition deployed solutions into long-term support and scale.
• Develop cloud-native architectures across Azure, AWS, or GCP.

Required Skills & Experience

Mandatory

• 6+ years of experience in software engineering, data engineering, or AI/ML.
• Strong hands-on experience building, deploying, and operating production-grade systems.
• Expert-level proficiency in Python for large-scale, high-performance applications.
• Proven delivery experience in client-facing and high-ambiguity environments.
• Solid foundation in distributed systems, microservices, APIs, and cloudnative architectures.
• Demonstrated ability to independently own and deliver complex, high-impact initiatives.
• Excellent communicator, effective with both technical teams and business stakeholders and should have worked directly with clients.

Desired / Preferred

• Hands-on experience with LLM APIs and prompt engineering, RAG architectures and vector databases, Agentic workflows and orchestration frameworks
• Experience integrating AI systems with enterprise data platforms.
• Exposure to AI ecosystem OpenAI, Claude, Cursor, Palantir, and many others along with Hyperscalers – Azure, AWS, GCP, and similar ecosystem.
• Experience with DevOps, CI/CD pipelines, and infrastructure automation.
• Consulting, global delivery, or field engineering experience.
• Prior Forward Deployed Engineer / Solutions Engineer / Field Engineer background.
• Experience building 0 1 AI or data products.
• Exposure to MLOps practices and model monitoring.
• Frontend or UI exposure for AI-driven applications.