Job description

SENIOR APPLIED AI ENGINEER ABOUT THE OPPORTUNITY Bedrock Talent is partnering with a well-funded, founder-led B2B AI company building mission-critical software for complex, highly regulated industries. Its platform applies large language models and natural language processing to dense, high-stakes information, transforming it into reliable and actionable workflows. This allows customers to make better decisions, reduce manual research and bring products to market faster. The company has approximately 18 employees, including a seven-person technical organization spanning Data, ML and Platform/Product Engineering. Engineers work closely with the founders, customers and one another, with very few organizational layers. THE ROLE We are looking for a Senior Applied AI Engineer who combines practical LLM and NLP experience with strong backend engineering skills. This is not a pure research position. You will build production systems, not just experiments or proofs of concept. You will own core AI capabilities end to end, from technical design and model selection through deployment, evaluation and iteration with users. The right person may come from a traditional ML engineering background or be an experienced backend engineer who has successfully built LLM-powered products and agentic workflows. A PhD or research-heavy background is not required. WHAT YOU’LL DO - Design, build and operate production-grade AI systems using LLMs, NLP and applied machine learning. - Develop agentic workflows that solve complex, real-world product problems. - Own core AI capabilities from initial experimentation through production deployment and ongoing improvement. - Collaborate with Product, Data and go-to-market stakeholders to translate customer needs into scalable technical solutions. - Select the appropriate models, frameworks and infrastructure for experimentation, evaluation, testing and monitoring. - Build reliable backend services and integrations around AI-powered product features. - Establish practical approaches to evaluating model quality, system reliability and user impact. - Work directly with users to test solutions, gather feedback and iterate quickly. - Make and communicate thoughtful tradeoffs between development speed, accuracy, reliability and scalability. WHAT WE’RE LOOKING FOR - Five or more years of professional software engineering, machine learning or applied AI experience. - Strong backend engineering skills, ideally with Python. - Experience building and operating production systems beyond the proof-of-concept stage. - Hands-on experience with LLMs, NLP and applied machine learning. - Experience using commercial, open-source or proprietary language models. - Experience designing or building agentic workflows. - Strong system-design, analytical and technical problem-solving skills. - A product-oriented mindset and comfort working with evolving requirements. - The ability to move quickly while maintaining a high standard for production quality. - Clear communication, intellectual honesty and a low-ego approach to collaboration. - A bachelor’s or master’s degree in computer science, engineering or a related field, or equivalent practical experience. NICE TO HAVE - Experience deploying AI or backend systems on AWS or another major cloud platform. - Familiarity with Docker and production containerization. - Experience with infrastructure as code, including Terraform or CloudFormation. - Experience in an early-stage or high-growth startup. - Experience working directly with customers or product users. - Exposure to data-intensive, enterprise or regulated-industry products. LOCATION AND WORKING MODEL The company is headquartered in New York City and prefers candidates who are based in or near NYC. There is flexibility for exceptional remote candidates. Remote employees should expect to spend approximately one week with the team in New York every few months. Candidates must already have authorization to work in the United States. The company does not currently support visa sponsorship or transfers. WHY CONSIDER THIS ROLE? - Own meaningful AI systems from architecture through production. - Work directly with a highly technical founding team. - Join a small organization where individual engineers have substantial influence. - Build practical LLM and agentic products used in real, high-stakes workflows. - Collaborate closely across AI, Data, Product and Platform Engineering. - Help shape the technical direction of a growing, well-capitalized AI company.

Requirements

Must-haves

We are looking for a Senior Applied AI Engineer who combines practical LLM and NLP experience with strong backend engineering skills.
Design, build and operate production-grade AI systems using LLMs, NLP and applied machine learning.
Develop agentic workflows that solve complex, real-world product problems.
Own core AI capabilities from initial experimentation through production deployment and ongoing improvement.
Collaborate with Product, Data and go-to-market stakeholders to translate customer needs into scalable technical solutions.
Select the appropriate models, frameworks and infrastructure for experimentation, evaluation, testing and monitoring.
Build reliable backend services and integrations around AI-powered product features.
Establish practical approaches to evaluating model quality, system reliability and user impact.
Work directly with users to test solutions, gather feedback and iterate quickly.
Make and communicate thoughtful tradeoffs between development speed, accuracy, reliability and scalability.
Five or more years of professional software engineering, machine learning or applied AI experience.
Strong backend engineering skills, ideally with Python.
Experience building and operating production systems beyond the proof-of-concept stage.
Hands-on experience with LLMs, NLP and applied machine learning.
Experience using commercial, open-source or proprietary language models.
Experience designing or building agentic workflows.
Strong system-design, analytical and technical problem-solving skills.
A product-oriented mindset and comfort working with evolving requirements.

Nice-to-haves

Experience deploying AI or backend systems on AWS or another major cloud platform.
Familiarity with Docker and production containerization.
Experience with infrastructure as code, including Terraform or CloudFormation.
Experience in an early-stage or high-growth startup.
Experience working directly with customers or product users.
Exposure to data-intensive, enterprise or regulated-industry products.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: ashby
Effort: quick