Applied AI Solution Engineer

Kearney; Bengaluru; On-site; INR 1,500,000 - 2,200,000; Full time

Benefits offered by this job

Mentorship from AI engineers

Client exposure to projects

Access to cutting-edge AI tools

Growth path toward advisory work

Job summary

Kearney Activate seeks an Applied AI Solution Engineer to design, build, and deploy AI-powered applications, primarily using LLMs, agents, and GenAI techniques. You will work in cross-functional teams on client projects, contributing to solution design, development, testing, and delivery with senior guidance.

You will gain exposure to end-to-end delivery, tool integration, and best practices while collaborating with clients and engineers to translate business needs into practical AI components.

Qualifications

• Hands-on experience building AI-powered applications with LLMs.
• Experience designing AI components for end-to-end solutions.
• Familiarity with retrieval-augmented generation and agents.

Responsibilities

• Design and deploy AI-driven applications leveraging LLMs and agents.
• Build and integrate AI components into microservices and APIs.
• Collaborate with clients and engineers to translate requirements into solutions.
• Troubleshoot and resolve technical issues during development and delivery.
• Share learnings and patterns to improve team practices.
• Keep up-to-date with new AI tools, models, and frameworks.

Skills

Python

SQL

APIs

Data pipelines

LLM APIs

GenAI concepts

RAG development

Embeddings

Vector stores

Cloud tools

Tools

Azure OpenAI

Gemini

Hugging Face

Anthropic

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 team 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

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.

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.

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.

Technical Problem‑Solving

• Contribute to solving technical issues encountered during development and implementation.
• Identify blockers and elevate complex challenges to senior engineers and R&D teams.
• Assist in documenting 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.

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 tools and 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.