Job Description
Applied AI Solution Engineer
Location- Bangalore ( Hybrid )
Role- Full Time
Experience 5+ years
About Kearney Activate
Kearney Activate is the business acceleration and enablement arm of Kearney Management Consulting, helping clients accelerate transformation through Data and AI.Our Data & AI business line bridges strategy, technology, and execution to deliver data-driven, AI-enabled,and cloud-powered transformations. We partner with leading platforms such as Microsoft, AWS,Snowflake, Databricks and Nvidia to help organizations build trusted data foundations, deploy intelligent solutions, and scale innovation.
We operate across four key focus areas:
- Advisory & Assurance Services: Driving strategy, governance, and change management to ensure impactful transformation.
- Data Services: Building trusted, high-quality data foundations using Agentic AI across engineering, architecture, and governance. Insights Services: Unlocking value through analytics, data science, and AI-driven storytelling for better decision-making.
- Asset Services: Developing reusable GenAI assets, accelerators, and AI-powered solutions that push the boundaries of innovation.
About the Role
As a Junior Applied AI Solution Engineer, 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.
You will work closely with senior engineers and client teams, gaining exposure to real-world AI solution engineering. 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. We do not train foundational models from scratch.
Key Responsibilities
1. AI Solution Development
- Assist in building AI-powered applications, especially those involving LLMs, retrieval-augmented generation, and autonomous agents.
- Support the design and hands-on implementation of end-to-end solutions with guidance from senior engineers.
- Help integrate AI components into microservices, APIs, and client-facing applications.
2. Agent & Workflow Development
- Support the creation of multi-step reasoning agents using LangGraph or LangChain Agents.
- Implement tool-calling, memory, and routing logic.
- Evaluate agent behaviour and improve reliability over iterations.
3. Client Collaboration & Communication
- Participate in conversations with clients to understand their challenges, use cases, and requirements.
- Help translate business needs into feasible AI/ML solution components.
- Support senior engineers in presenting solution concepts and explaining AI capabilities in accessible terms.
4. Technical Problem-Solving
- Contribute to solving technical issues encountered during development and implementation.
- Identify blockers and escalate complex challenges to senior engineers and R&D teams.
- Assist in documenting learnings and reusable patterns for future solutions.
5. 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 a\ect the user experience.
6. 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.
Technical Skills
You have hands-on experience or strong foundational knowledge in several of the following areas:
- Python programming and data technologies (SQL, APIs, basic data pipelines).
- Building small-scale microservices or automation scripts.
- Working with LLM APIs (Azure OpenAI, Gemini, Hugging Face, Anthropic).
- Exposure to GenAI concepts (prompting, embeddings, finetuning, 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.
Client-Facing Mindset
Even at a junior level, you should feel comfortable and excited to grow in these areas:
- Communicating clearly with non-technical audiences.
- Translating business needs into technical requirements (with support).
- Understanding business processes and identifying where AI can add value.
Personal Traits
- 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 toolsand methods.
- Ethical & Responsible: You understand the importance of safe, fair, and responsible AI implementation.
Nice to Have
- 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
What We Offer
- 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.
No Referrers Available
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