Founding AI Engineer / Member of Technical Staff

About the Opportunity

FDE Team builds and deploys Forward Deployed Engineering teams that embed directly into customer organizations, working inside their systems, technology stacks, and workflows from day one. Our engineering pods work across AI, Core Engineering, Sales Ops, Marketing Growth, and Cloud Cost Optimization, helping companies modernize technology, automate operations, and deploy production-ready systems in weeks.

This is an opportunity for exceptional engineers who enjoy building from 0→1, solving ambiguous and technically challenging problems, and shipping production-grade AI systems in a fast-moving environment.

Backed by SA Technologies, a global technology organization with enterprise delivery expertise across North America, Europe, and Asia Pacific.

Founding AI Engineer / Member of Technical Staff

Job Title: Founding AI Engineer / Member of Technical Staff (MTS)
Department: AI / Core Engineering
Employment Type: Full-Time
Location: San Francisco, California
Work Model: Onsite
Travel: Customer travel may be required based on engagement needs

About the Role

FDE Team is looking for an exceptional Founding AI Engineer / Member of Technical Staff to build and scale production-grade AI systems from the ground up.

This is a deeply hands-on engineering role combining production AI, backend engineering, distributed systems, data infrastructure, and product development. You will work on complex problems where the solution is not always clearly defined and will have significant ownership over architecture, implementation, deployment, and technical direction.

We are looking for engineers who can move comfortably between AI systems and traditional software engineering—someone who can build an intelligent workflow or agent while also designing the APIs, data infrastructure, distributed services, evaluation systems, and production architecture required to make it reliable.

This is not a research-only or architecture-only position. You will be expected to write production code, build systems, experiment rapidly, and own what you ship.

What You'll Do

• Design, build, and operate production-grade AI applications and platforms.
  
• Take new products and technical capabilities from 0→1, prototype through production and scale.
  
• Build AI-powered applications using LLMs, RAG, agents, retrieval systems, and intelligent workflows.
  
• Architect scalable backend services, APIs, distributed systems, and data pipelines.
  
• Develop production software using Python and other modern programming languages.
  
• Work with both structured and unstructured data across databases, search, retrieval, and data-processing systems.
  
• Build model and application evaluation frameworks, guardrails, monitoring, observability, and testing infrastructure.
  
• Design reliable orchestration and tool-use patterns for agentic AI systems.
  
• Integrate foundation models and AI services with customer and enterprise systems.
  
• Improve the performance, reliability, scalability, and security of production AI applications.
  
• Rapidly prototype new approaches, evaluate results, and convert successful experiments into maintainable production systems.
  
• Diagnose complex problems across models, applications, data, infrastructure, and distributed services.
  
• Make architecture and technology decisions while balancing development speed with long-term maintainability.
  
• Work closely with senior engineers, product stakeholders, customers, and business teams to turn ambiguous requirements into working software.
  
• Help establish engineering standards, architecture patterns, and technical best practices as the organization scales.
  

What We're Looking For

• 6+ years of professional software engineering experience with significant ownership of production systems.
  
• Strong hands-on programming experience with Python and one or more of Go, Java, C++, or TypeScript/JavaScript.
  
• Strong foundations in backend engineering, distributed systems, APIs, databases, data structures, algorithms, and system design.
  
• Hands-on experience building production applications using LLMs, Generative AI, RAG, AI agents, or related AI/ML technologies.
  
• Experience taking complex products or systems from prototype into production.
  
• Strong understanding of modern data architectures involving structured and unstructured information.
  
• Experience with cloud platforms such as AWS, GCP, or Azure.
  
• Experience with modern production infrastructure, including containers, CI/CD, monitoring, observability, and automated testing.
  
• Strong debugging and performance-analysis capabilities.
  
• Ability to operate independently and make technical decisions in ambiguous environments.
  
• Strong communication skills and the ability to collaborate with technical and non-technical stakeholders.
  
• Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, AI/ML, or another highly technical discipline, or equivalent practical experience.
  

Preferred Qualifications

• Previous experience as a Founding Engineer, Member of Technical Staff, Staff Engineer, Principal Engineer, or early-stage startup engineer.
  
• Experience building products in an early-stage / 0→1 startup environment.
  
• Experience with agentic AI systems, tool use, multi-agent workflows, or LLM orchestration.
  
• Experience with RAG, embeddings, semantic search, vector databases, knowledge graphs, or hybrid retrieval.
  
• Experience designing LLM/AI evaluation systems, including quality measurement, regression testing, guardrails, or human-in-the-loop workflows.
  
• Experience with high-scale distributed systems, event-driven architectures, streaming, or data-intensive applications.
  
• Experience building secure and auditable systems handling sensitive or regulated information.
  
• Experience at a high-growth technology, AI, or product engineering organization.
  
• Demonstrated ability to provide technical leadership while remaining a highly hands-on individual contributor.
  

What Makes This Opportunity Different

You'll be joining an environment where engineers are expected to do more than implement predefined tickets. You'll help define the problem, determine the architecture, build the solution, measure whether it works, deploy it, and improve it based on real-world usage.

The ideal candidate combines the mindset of a founding engineer with the technical depth of a senior/staff-level individual contributor—comfortable operating across AI, backend systems, infrastructure, and product engineering.

We particularly value engineers who have demonstrated 0→1 ownership, strong technical judgment, high engineering standards, and the ability to deliver in environments where requirements evolve quickly.