What are the responsibilities and job description for the AI Engineer position at MCS Group - USA | Your Specialist Recruitment Firm?
Senior AI Engineer
📍 Massachusetts (Hybrid or Remote Options Available)
Note: This role is not live yet but is expected to open in the coming months. We're proactively connecting with strong candidates ahead of the official launch.
This is a full time role with no sponsorship. Agencies please do not submit candidates.
We're partnering with a fast-growing tech company building software that helps engineering and manufacturing teams make smarter decisions before anything is built, giving real-time visibility into cost, feasibility and supply chain impact.
They're looking for a Senior AI Engineer to help embed AI directly into their platform and drive the next generation of intelligent product capabilities.
This is a hands-on, high-impact role where you'll work at the intersection of LLMs, traditional ML and scalable data systems, helping bring intelligent features into production.
What You'll Be Doing
- Build and deploy scalable AI/ML solutions, with a focus on LLM-driven product features and real-world applications
- Develop intelligent workflows using modern LLM frameworks (e.g. RAG, copilots, agent-based systems)
- Work cross-functionally with product and engineering teams to turn business needs into impactful AI capabilities
- Implement best practices across MLOps/LLMOps, including evaluation, monitoring, and performance optimization
- Contribute to data strategy and architecture, while supporting and mentoring others in advancing AI adoption
What They're Looking For
- 7 years in software engineering, including experience across AI/ML and exposure to LLM-based applications
- Strong Python skills with experience building and scaling data and ML pipelines
- Hands-on experience working with LLMs, including prompt design and frameworks used for building GenAI applications
- Solid understanding of data engineering fundamentals (e.g. pipelines, streaming, orchestration tools)
- Experience applying MLOps/LLMOps practices such as model evaluation, monitoring, and deployment workflows
- Ability to collaborate across product and engineering teams, with a track record of delivering AI features end-to-end
- Experience with cloud platforms such as AWS, GCP or Azure
- Experience with ML frameworks such as TensorFlow, PyTorch or scikit-learn
- Previous experience mentoring or leading engineers is a plus
Why This Role?
- Work on real-world AI products, not just experimentation
- High visibility and impact across product and engineering
- Opportunity to shape how AI is embedded into a modern platform
- Collaborative, fast-moving environment with strong technical ownership
If you're excited about building AI systems that actually make it into production (and matter to users), this is worth a conversation.
To speak in confidence about this opportunity please contact apply via the link