Forward Deployed Engineer
EnigmaAbout the role
Forward Deployed Engineer | Python | API's | AWS | Docker | Kubernetes | Hybrid | San Francisco, CA
The Opportunity
We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between cutting-edge generative AI models and the customers who rely on them. You will work directly with pharmaceutical and biotechnology organisations to deploy, integrate, and optimise AI technology within their scientific workflows.
This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world challenges in drug discovery and protein engineering.
You will partner closely with customers to understand their technical environments and ensure seamless integration of our generative biology platform into their existing systems. You will own the full lifecycle of customer deployments, from initial technical discovery through production implementation and act as the voice of the customer by providing feedback to internal product, engineering, and research teams.
About the Organisation
We are developing next-generation AI models that advance the understanding and application of biology. Our multidisciplinary team brings together expertise in machine learning, computational biology, software engineering, and scientific research to tackle complex challenges at the intersection of AI and life sciences.
We value scientific excellence, collaboration, continuous learning, and interdisciplinary innovation. Our teams work across multiple international locations, with regular opportunities to collaborate in person and remotely.
We are looking for curious, mission-driven individuals who are excited by ambitious technical challenges and motivated to create meaningful real-world impact.
About You
You will ideally have the following:
A strong academic background in Computer Science, Machine Learning, Artificial Intelligence, or another quantitative discipline (BSc, MSc, or PhD)
Experience building systems that interact with large AI models through APIs
Hands-on experience designing, deploying, and maintaining infrastructure for large-scale model serving
Experience deploying AI solutions for external customers and translating complex technical concepts for both technical and non-technical stakeholders
Strong knowledge of cloud infrastructure, particularly AWS, with exposure to platforms such as Azure or Google Cloud
Experience with Docker, Kubernetes, CI/CD pipelines, and cloud-native architectures.
Excellent communication and collaboration skills, with the ability to work effectively across technical and business teams
A proactive, adaptable mindset and the ability to manage multiple customer engagements in a fast-paced environment
Desirable Experience
The following would be advantageous:
Experience applying machine learning within computational biology, protein design, or related life sciences
Contributions to generative AI research, open-source software, publications, or production AI systems
Experience building secure, reliable enterprise software that meets production requirements.
Familiarity with pharmaceutical or biotechnology environments, including scientific workflows, data governance, or regulatory considerations
Key Responsibilities
Customer Deployment & Integration
Lead end-to-end deployment of AI models into customer environments
Design and implement production-ready API integrations, data pipelines, and model-serving infrastructure
Work closely with customer engineering and scientific teams to gather requirements, troubleshoot issues, and deliver technical solutions
Ensure deployments meet enterprise standards for security, scalability, reliability, and performance
Customer Success & Product Feedback
Serve as the primary technical contact for assigned customers
Build trusted relationships with scientific and engineering stakeholders.
Gather customer feedback and translate it into actionable recommendations for internal product and engineering teams
Contribute to product roadmap discussions by sharing insights from real-world deployments.
Develop technical documentation, implementation guides, and best-practice resources
Professional Development
Stay current with advances in machine learning infrastructure, cloud technologies, and model-serving practices
Build domain knowledge in computational biology and related scientific areas relevant to the platform
Contribute to internal knowledge sharing through technical presentations, documentation, and learning sessions
Benefits
We offer a competitive compensation and benefits package, which may include:
Private health insurance
Retirement or pension contributions
Generous annual leave and family-friendly policies
Hybrid working arrangements
Opportunities for travel and international collaboration
A collaborative environment with opportunities to work on cutting-edge AI applications in life sciences
We are committed to fostering an inclusive workplace and welcome applications from candidates of all backgrounds. We believe that diverse perspectives, experiences, and ideas are essential to building exceptional teams and delivering meaningful innovation.
Forward Deployed Engineer | Python | API's | AWS | Docker | Kubernetes | Hybrid | San Francisco, CA
Responsibilities
- Lead end-to-end deployment of AI models into customer environments
- Design and implement production-ready API integrations, data pipelines, and model-serving infrastructure
- Work closely with customer engineering and scientific teams to gather requirements, troubleshoot issues, and deliver technical solutions
- Serve as the primary technical contact for assigned customers
- Build trusted relationships with scientific and engineering stakeholders
- Gather customer feedback and translate it into actionable recommendations for internal product and engineering teams
- Stay current with advances in machine learning infrastructure, cloud technologies, and model-serving practices
Qualifications
- Strong academic background in Computer Science, Machine Learning, Artificial Intelligence, or another quantitative discipline
- Experience building systems that interact with large AI models through APIs
- Hands-on experience designing, deploying, and maintaining infrastructure for large-scale model serving
- Strong knowledge of cloud infrastructure, particularly AWS
- Experience with Docker, Kubernetes, CI/CD pipelines, and cloud-native architectures
- Excellent communication and collaboration skills
Benefits
- Private health insurance
- Retirement or pension contributions
- Generous annual leave and family-friendly policies
- Hybrid working arrangements
- Opportunities for travel and international collaboration
Skills mentioned
About Enigma
Here at Enigma, we specialize in Generative AI recruitment, specifically focused on Machine Learning and Software Engineering disciplines. With a combined experience of 20+ years, we understand the intricacies of finding the perfect role as well as the right talent for your team. But what sets Enigma apart? Our consultative approach. We don't just match candidates with job openings; we guide candidates, founders, and hiring managers through the recruitment process. Our value-added services go beyond traditional recruitment efforts, offering services such as recruitment process structuring, salary benchmarking, share allocation, CV reviews and so much more. We're more than recruiters – we're partners in your success journey. Our mission is not only to connect you with exceptional talent and companies but also to support your growth and success every step of the way. We're committed to your success. Let us partner with you to connect you with people and companies alike, that will drive growth and innovation for years to come.