Forward Deployment Engineer

Company: Tenarai

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Enterprise

Company Type: Product & Service

Business Model: B2B

Funding Stage: Series A

Industry: Information Technology

Salary Range: ₹ 30-45 Lacs PA

Job Description We are looking for a Forward Deployment Engineer (FDE) – AI/GenAI who can work closely with customers to design, build, deploy, and scale production-ready AI solutions.

The role combines AI/GenAI engineering, solution architecture, customer engagement, and production deployment. You will take AI solutions from POC to production and ensure they are secure, scalable, reliable, and measurable.

Key Responsibilities

• Design and deploy production-ready AI and GenAI solutions in customer environments.
• Build Agentic AI applications using RAG, LLMs, tool/function calling, orchestration, and multi-step workflows.
• Understand customer requirements and convert business problems into practical technical solutions.
• Work directly with customer engineering and business teams during discovery, implementation, and rollout.
• Take AI solutions from POC to production and drive adoption.
• Design reliable systems with proper monitoring, logging, error handling, retries, fallbacks, and safe failure mechanisms.
• Optimize AI applications for performance, latency, scalability, and cost.
• Establish deployment, evaluation, and monitoring frameworks for AI systems.
• Collaborate with AI Engineers, Platform Engineers, and Product/Research teams.
• Communicate technical architecture, risks, trade-offs, and progress to technical and non-technical stakeholders.
• Ensure smooth handover of deployed solutions to customer/platform teams with proper documentation and operational support plans.
• Mentor engineers on production-grade AI development and deployment practices.

Required Skills

• 5+ years of experience in Software Engineering / AI Engineering / Solutions Engineering / Technical Consulting.
• Strong experience with Python and modern software development practices.
• Hands-on experience building and deploying GenAI/LLM applications.
• Strong understanding of RAG, Agentic AI, LLM orchestration, prompt engineering, and tool/function calling.
• Experience with APIs, microservices, cloud platforms, and production deployments.
• Experience working with customers or cross-functional teams in a delivery environment.
• Strong understanding of system design, scalability, reliability, monitoring, and observability.
• Ability to convert ambiguous business requirements into practical technical architectures.

Good to Have

• Experience with Azure / AWS / GCP.
• Experience with vector databases and AI frameworks.
• Experience with FastAPI, LangChain, LlamaIndex, Semantic Kernel or similar frameworks.
• Experience with LLM evaluation and AI observability.
• Experience with enterprise AI deployments.
• Experience mentoring engineers or leading technical delivery.