Forward-Deployed AI Engineer
About this role
This role addresses the need to deploy advanced, end-to-end agentic AI solutions within mission-critical workflows for Fortune 500 enterprises. The team at Turing focuses on closing the loop between frontier AI research and real-world enterprise deployment by generating high-quality datasets and building robust systems. This position is crucial for shaping how Turing delivers applied AI, focusing on solving complex, enterprise-grade problems that drive measurable business impact. It is designed for individuals who thrive in an intense, intellectually challenging environment where they can define the frontier of applied AI.
The Forward-Deployed AI Engineer will own outcomes completely, starting from identifying high-value customer problems and defining the technical architecture through to building and deploying production systems. This involves developing sophisticated generative AI solutions that deliver tangible return on investment within large institutions. The individual will be responsible for leading solutions from initial discovery through final deployment, maintaining accountability for all aspects including reliability, security, and cost.
This role is ideal for a highly self-directed engineer who possesses strong business acumen and the ability to navigate ambiguity when working directly with senior client leaders. Success in this role depends on the capacity to build processes where none exist, effectively writing the playbook for Enterprise AI while maintaining a strong focus on client needs and technical excellence.
What you will do
- Work directly with customers to identify high-value opportunities and translate complex business needs into clear technical direction.
- Architect and build production AI systems, encompassing multi-agent workflows, orchestration, tool use, context engineering, memory and state, and RAG.
- Develop the necessary APIs, data pipelines, integrations, and distributed systems to ensure these AI solutions operate reliably at scale.
- Own the entire outcome for client solutions, managing evaluation, observability, security, latency, scalability, and cost.
- Lead solutions from discovery through deployment, ensuring measurable impact for the client.
- Help establish processes and playbooks for Enterprise AI based on expertise and technical depth.
What you need
- Possess deep production engineering experience, typically 8+ years, building and operating sophisticated software systems.
- Demonstrate expertise in core areas such as Python, backend systems, APIs, databases, distributed systems, and cloud infrastructure.
- Must have hands-on experience building production LLM and agent systems utilizing orchestration, tool use, context engineering, memory, and state.
- Require strong retrieval depth, including practical knowledge of embeddings, vector and hybrid search, reranking, and evaluation.
- Must have a proven track record of owning end-to-end systems, covering evaluation, observability, reliability, security, latency, scalability, and cost.
- Need exceptional customer and technical leadership skills to navigate ambiguity and communicate effectively with senior executives.
Nice to have
- Experience with specific enterprise workflows
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?
The work model is hybrid, requiring employees to be in the office three days per week. Candidates must currently be based in either Bengaluru or Hyderabad.
What is the expected level of ownership in this role?
The role requires exceptional ownership and accountability, as the engineer will have the authority to own the outcome for the client and make a real-world impact through their work.
What technical areas are central to building solutions?
The role involves architecting systems like multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG).
How is the team structure described?
The role joins the initial team of Forward-Deployed Engineers, operating with the speed, focus, and ownership of a rapidly scaling startup.