Forward-Deployed AI Engineer
About this role
This role is ideal for an engineer who thrives on high ownership and intellectually challenging problems. The Forward-Deployed AI Engineer will join the Enterprise AI business unit at Turing, focusing on applying advanced AI to solve complex, mission-critical problems for Fortune 500 enterprises across various sectors. The team builds and deploys end-to-end agentic AI systems within workflows, bridging the gap between frontier AI research and real-world enterprise deployment. Candidates who enjoy defining the frontier of applied AI, translating ambiguous business needs into technical direction, and taking full accountability for outcomes will find this work highly engaging.
The engineer will be responsible for identifying valuable customer problems, shaping the overall architecture, and subsequently building robust, production-grade AI systems. This involves developing generative AI solutions that deliver measurable impact and return on investment within large institutions. It is an intense, demanding environment that requires a high degree of autonomy and technical depth.
Success in this role depends on the ability to operate with startup speed, creating processes where none exist, and leading solutions from initial discovery through to scaled deployment. This position is for someone who seeks to build beyond current capabilities and directly influence how large organizations utilize AI.
What you will do
- Work directly with customers to navigate ambiguity and uncover high-value opportunities.
- Translate complex business needs into clear technical direction for AI solutions.
- Architect and build production AI systems, including multi-agent workflows, orchestration, and tool use.
- Implement systems involving context engineering, memory and state management, and Retrieval-Augmented Generation (RAG).
- Own the entire outcome, managing evaluation, observability, security, reliability, latency, scalability, and cost.
- Lead solutions from discovery through deployment, ensuring measurable impact for the client.
- Help establish the playbook for Enterprise AI by applying expertise to define processes.
What you need
- Possesses deep production engineering experience, typically spanning over eight years in building and operating sophisticated software systems.
- Demonstrates expertise in core backend technologies such as Python, APIs, databases, distributed systems, and cloud infrastructure.
- Requires hands-on experience building production LLM and agent systems utilizing orchestration, tool use, context engineering, memory, and state.
- Must have strong retrieval depth, including practical knowledge of embeddings, vector and hybrid search, reranking, and diagnosing retrieval quality.
- Has a proven track record of taking complex systems from initial architecture through to full deployment and scale.
- Requires exceptional customer and technical leadership skills to navigate unfamiliar environments and challenge assumptions constructively.
Nice to have
- Experience with multi-agent workflows
- Experience with retrieval-augmented generation (RAG)
Benefits
- Hybrid work model (3 days per week in office)
Skills and tech stack
Questions candidates ask
What is the work model for this role?
This role operates on a Hybrid model, requiring three days per week to be in the office. Candidates must currently be based in either Bengaluru or Hyderabad.
What is the expected level of ownership in this position?
The role demands exceptional ownership and accountability, as the engineer will own the outcome for the client and make a real-world impact. This involves leading solutions from discovery through deployment.
What is the core technology focus?
The work involves architecting and building production AI systems, focusing on multi-agent workflows, orchestration, tool use, context engineering, memory and state, and RAG.
What is the team structure like?
The engineer will join the initial team of Forward-Deployed Engineers, operating with the speed and focus of a rapidly scaling startup.