Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Engineer (Applied AI / ML) in the United States.
This role offers an exciting opportunity to work at the forefront of applied AI and machine learning, delivering innovative solutions for complex business challenges. You will collaborate with cross-functional teams to design, implement, and optimize AI-driven applications, while mentoring team members and influencing technical strategy. The position emphasizes hands-on development, experimentation with emerging AI tools, and engagement with clients to ensure impactful solutions. You will work on diverse projects, from RAG applications to enterprise AI deployments, and contribute to shaping the technology landscape for both internal and client-facing initiatives. This is ideal for engineers who thrive in fast-paced, collaborative environments and enjoy balancing technical excellence with strategic impact.
Accountabilities:
- Lead and contribute to software development projects across the full SDLC, with a focus on Applied AI/ML.
- Mentor and guide team members while promoting best practices in software engineering and AI application.
- Collaborate with clients and internal stakeholders to design and present AI/ML solutions.
- Experiment with emerging AI technologies, cloud offerings, and productivity tools to enhance project outcomes.
- Develop copilots, RAG applications, and other AI-driven solutions while ensuring scalable and maintainable architectures.
- Implement CI/CD pipelines, integration architectures, and data management strategies for enterprise deployments.
- Apply sound architectural principles including SOA, microservices, and separation of concerns in solution design.
Requirements
- 4–6 years of software development experience, including team-based projects.
- Strong proficiency in ML/Applied AI tools and patterns, including LLMs, MLOps, and RAG workflows.
- Experience with AI models such as OpenAI, ChatGPT, Claude, Amazon Bedrock, LLaMA, or similar, with an understanding of use case applicability.
- Knowledge of vector databases, embeddings, and graph databases.
- Hands-on experience with enterprise application integration, authentication/authorization methods, and data management.
- Familiarity with agile methodologies such as Scrum, Kanban, or XP.
- Solid software engineering foundations, including OOP, functional programming, and architectural best practices.
- Ability to communicate effectively with client leadership and technical stakeholders.
- Experience balancing feature development with technical debt management in complex projects.
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