Kearney Activate AI Engineer

Kearney•Boston, MA

About The Position

As an AI Engineer at Kearney Activate , you will work as part of a cross-functional teams to design, build, and deploy AI-driven applications. Particularly those leveraging Large Language Models (LLMs), agents, and other modern AI techniques. This is a hands-on, client-facing engineering role where you will contribute to solution design, development, testing, and delivery. In this position we would expect you to be able to lead engineering teams while also act as an individual delivery contributor in delivery when the project requires. As you grow in the role, you will take on more ownership, from end-to-end delivery to advising clients on AI opportunities and best practices. Our teams primarily build solutions using existing foundational models (closed and open source), sometimes with light fine-tuning.

Requirements

You have hands-on experience and strong foundational knowledge in several of the following areas:
Python programming and data technologies (SQL, APIs, basic data pipelines).
Building small-scale micro services or automation scripts.
Working with LLM APIs (Azure OpenAI, Gemini, Hugging Face, Anthropic).
Exposure to GenAI concepts (prompting, embeddings, fine tuning, vector search)
Basic experience with RAG development and knowledge retrieval
Understanding of model fine-tuning, vector stores, embeddings concepts.
Ability to design simple solution architectures using Python & cloud tools.
Strong analytical and problem-solving mindset.
Willingness to learn new technologies when the project requires it.
Communicating clearly with non-technical audiences.
Translating business needs into technical requirements with minimal handholding.
Understanding business processes and identifying where AI can add value.
Adaptable & Self-Motivated\: You are proactive, resourceful, and able to operate independently with minimal handholding.
Passionate & Positive\: You are genuinely excited about AI and its potential to transform industries.
Creative & Curious\: You keep up with AI developments and enjoy experimenting with new tools and methods.
Ethical & Responsible\: You understand the importance of safe, fair, and responsible AI implementation.

Nice To Haves

Experience with building data pipelines, preparing and indexing datasets, and implementing embedding generation and retrieval evaluation for GenAI applications
Exposure to MLOps, Docker, CI/CD, or cloud platforms (AWS/GCP/Azure)
Hands-on work with agent workflows or multi-step reasoning models
“Vibe coding” skills - fast prototyping, AI-assisted development, improvisational coding

Responsibilities

AI Solution Development Contribute to building AI-powered applications, especially those involving LLMs, retrieval-augmented generation, and autonomous agents.
Lead the design and hands-on implementation of end-to-end solutions with guidance from senior engineers.
Integrate AI components into micro services, APIs, and client-facing applications.
Agent & Workflow Development Contribute to the creation of multi-step reasoning agents using Lang Graph or LangChain Agents.
Implement tool-calling, memory, and routing logic.
Evaluate agent behavior and improve reliability over iterations.
Client Collaboration & Communication Lead conversations with clients to understand their challenges, use cases, and requirements.
Translate business needs into feasible AI/ML solution components.
Comfortable and experienced in presenting solution concepts and explaining AI capabilities in accessible terms.
Technical Problem-Solving Solve technical issues encountered during development and implementation.
Identify blockers and escalate complex challenges to senior engineers and R&D teams.
Document learnings and reusable patterns for future solutions.
Cross-Functional Collaboration Work collaboratively with technical and non-technical teams to ensure solutions are aligned with client expectations.
Provide input into product, data, and design discussions where AI components affect the user experience.
Continuous Learning & Growth Stay informed about new models, AI tools, frameworks, and best practices.
Proactively learn new technologies and explore innovative ways to apply AI to real-world problems.
Experiment with new open-source models, orchestration frameworks, and retrieval techniques.
Share findings and help improve team practices.

Benefits

Direct experience building real-world AI applications.
Mentorship from experienced AI engineers and architects.
Opportunities to work directly with clients across industries.
Access to cutting-edge AI tools, platforms, and training.
A growth path toward leading solution delivery and advisory work
paid time off
401(k) match and profit sharing
medical, dental and vision coverage
healthcare concierge
backup child/adult care
annual employer HSA contribution
home office stipend
subsidized Gympass and annual wellness program
leaves of absence when needed to support employees’ physical, mental, and emotional well-being