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Tech Stack
Tools & technologiesAWSAzureCloudGoGoogle Cloud PlatformJavaScriptPythonPyTorchTensorflowTypeScript
About the role
Key responsibilities & impact- Partner directly with client stakeholders to understand requirements, constraints, and business objectives.
- Lead the technical design and hands-on implementation of custom AI systems—including model integration, data pipelines, APIs, and deployment infrastructure.
- Rapidly prototype and iterate with clients in live environments.
- Build and deploy ML/AI solutions using technologies like Python, TensorFlow/PyTorch, LangChain, and cloud-native tools.
- Integrate LLMs and other generative models into client products and workflows.
- Support model fine-tuning, prompt engineering, and evaluation pipelines where applicable.
- Work with internal teams (product, design, research) to shape reusable components and frameworks based on deployment experiences.
- Contribute client feedback and frontline insights to improve service delivery and product strategy.
- Advise client technical teams on best practices for AI/ML development and deployment.
- Deliver hands-on workshops, documentation, and training to enable long-term client success.
- Guide clients through infrastructure and architecture decisions (e.g., cloud, security, scalability).
Requirements
What you’ll need- 2+ years of software engineering experience, ideally in full-stack or backend-focused roles.
- Hands-on experience delivering real-world ML/AI projects, either independently or in collaboration with data science teams.
- Strong programming skills (Python required; familiarity with JavaScript/TypeScript, Go, or similar a plus).
- Comfort with modern cloud platforms (AWS, GCP, or Azure) and CI/CD workflows.
- Excellent communication and client interaction skills.
- Experience with LLMs (e.g., OpenAI, Anthropic, Cohere), vector search, or prompt engineering (preferred).
- Prior consulting, professional services, or customer-facing technical roles (preferred).
Benefits
Comp & perks- Competitive compensation (salary + deployment bonuses or client uplift incentives).
- Equity options in a growing AI services company.
- Flexibility to work across industries and problem domains.
- A collaborative, mission-driven team passionate about the real-world impact of AI.