Senior AI Engineer (Hybrid)

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Bangalore, Bengaluru Urban, Karnataka, IND
Hybrid
Senior level
Digital Media • Internet of Things • Software
The Role
Leads the design, development, and operation of machine learning, LLM, and agentic systems for learner products and internal workflows. Owns architecture, reliability, security, cost, performance, evaluation, and observability of production AI services. Establishes engineering standards, reviews designs and code, mentors engineers, selects models and frameworks, and guides adoption of emerging AI technologies. Collaborates with product, data science, design, and learning teams to deliver secure, scalable solutions.
Summary Generated by Built In

Job Title 

Senior AI Engineer (Hybrid)

Job Description

The Senior AI Engineer leads the design, build and operation of the machine learning models, large language model (LLM) services and agentic systems that drive Kaplan’s AI strategy. Your remit spans learner-facing products and internal AI-first business processes. You will be a technical reference point for the AI Engineering team, owning the design of the systems you build and helping set the standard for how we deliver reliable, secure and scalable AI services.


As the Senior AI Engineer, you will:

  • Lead the design, development and delivery of machine learning, LLM and agentic solutions for learner products and internal business workflows.
  • Architect agentic workflows, including tool use, structured outputs, multi-agent orchestration and human-in-the-loop patterns.
  • Champion engineering standards and best practice, and review the designs and code of other engineers.
  • Own the reliability, cost, security and performance of AI services in production.
  • Build and maintain evaluation tooling and observability for models and LLM-based systems.
  • Mentor AI Engineers and help grow our engineering capability.
  • Collaborate with teams across Kaplan, including product, data science, design and learning teams, to translate requirements into technical direction.
  • Stay current with new AI tools and techniques and set direction on their practical adoption.

Detailed responsibilities

Technical leadership and mentoring

  • Set and champion standards for engineering quality, code review and reusable patterns.
  • Lead the technical approach on ambiguous or novel problems.
  • Own the design of the systems you build and shape architectural decisions across the AI platform, aligned with enterprise architecture.
  • Mentor and develop AI Engineers through review, pairing and technical guidance.

Model and agent development

  • Lead algorithm and framework selection, and design retrieval and grounding strategies, prompts and embeddings.
  • Design, build and evaluate agentic workfl ows using frameworks such as Microsoft Agent Framework.
  • Evaluate models and LLM-based systems using agreed metrics and methods, including golden datasets, LLM-as-judge evaluation, and tracing and observability tooling.
  • Partner with data science colleagues, who own modelling and evaluation

Innovation and growth

  • Assess emerging techniques and paradigms and set direction on their practical adoption.
  • Champion new ideas by building prototypes and translating research into tangible solutions.
  • Share fi ndings with product and learning stakeholders with clear impact statements.

You’ll also carry out other duties, within the broad scope and spirit of your role, as requested by your manager. Our business continuously evolves, so your role will too.


What you might be doing now; Your current role, or recent roles, may be:

  • AI Engineer at Kaplan, ready to step up
  • Senior Machine Learning Engineer
  • Senior Software Engineer leading AI features
  • Machine Learning Engineer leading the delivery of LLM or agentic systems

What you’ll bring to the role

This role suits an experienced, pragmatic engineer who leads by example: someone who balances rapid experimentation with production-level rigour and raises the standard of those around them.


You will have:

  • 5+ years’ experience in software or machine learning engineering.
  • Substantial experience (typically 2+ years) building and operating LLM-based or agentic systems in production.
  • Strong Python skills and knowledge of ML libraries (PyTorch, TensorFlow, scikit-learn).
  • Experience with agent and LLM frameworks (e.g. Microsoft Agent Framework, LangGraph) and prompt engineering.
  • Strong MLOps experience: CI/CD, container orchestration and infrastructure-as-code, with cloud platforms (Azure preferred).
  • Knowledge of NoSQL/document databases (e.g. Azure Cosmos DB) and vector search (e.g. Azure AI Search), plus a solid grounding in relational/SQL database design and querying.
  • Experience leading technical decisions, mentoring engineers and reviewing designs and code.
  • A strong understanding of data privacy, security and responsible AI, and the ability to explain complex ideas to non-specialists.

Desirable

  • Experience with Google’s agent platform (Gemini Enterprise Agent Platform/Vertex AI, including the Agent Development Kit).
  • Familiarity with agent interoperability standards such as the Model Context Protocol (MCP) and Agent2Agent (A2A).
  • Additional programming languages such as C# and the .NET framework.
  • Experience with education-specific standards such as xAPI, LTI or LMS plug-ins.

How you can build your career at Kaplan

From this role, your potential paths for career progression at Kaplan include:

  • Principal AI Engineer, deepening technical expertise as a senior individual contributor
  • AI Platform Lead, owning our AI platform and engineering standards
  • Head of AI Engineering, leading the engineering function

Location

Bangalore, KA, India

Additional Locations 

Employee Type

Employee

Job Functional Area 

IT Operations

Business Unit

00092 Kaplan Health

Diversity & Inclusion Statement:

Kaplan is committed to cultivating an inclusive workplace that values diversity, promotes equity, and integrates inclusivity into all aspects of our operations. We are an equal opportunity employer and all qualified applicants will receive consideration for employment regardless of age, race, creed, color, national origin, ancestry, marital status, sexual orientation, gender identity or expression, disability, veteran status, nationality, or sex. We believe that diversity strengthens our organization, fuels innovation, and improves our ability to serve our students, customers, and communities. Learn more about our culture here.

Kaplan considers qualified applicants for employment even if applicants have an arrest or conviction in their background check records. Kaplan complies with related background check regulations, including but not limited to, the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.  There are various positions where certain convictions may disqualify applicants, such as those positions requiring interaction with minors, financial records, or other sensitive and/or confidential information.

Kaplan is a drug-free workplace and complies with applicable laws. 

Skills Required

  • 5+ years of experience in software engineering or machine learning engineering
  • 2+ years of experience building and operating LLM-based or agentic systems in production
  • Strong Python skills
  • Knowledge of PyTorch, TensorFlow, and scikit-learn
  • Experience with agent and LLM frameworks such as Microsoft Agent Framework or LangGraph
  • Experience with prompt engineering
  • Strong MLOps experience, including CI/CD, container orchestration, and infrastructure as code
  • Experience with cloud platforms, preferably Azure
  • Knowledge of NoSQL or document databases such as Azure Cosmos DB
  • Experience with vector search such as Azure AI Search
  • Grounding in relational and SQL database design and querying
  • Experience leading technical decisions, mentoring engineers, and reviewing designs and code
  • Understanding of data privacy, security, and responsible AI
  • Ability to explain complex technical concepts to non-specialists
  • Experience with Google agent platforms, Gemini Enterprise Agent Platform, Vertex AI, or the Agent Development Kit
  • Familiarity with Model Context Protocol and Agent2Agent interoperability standards
  • Experience with C# and the .NET framework
  • Experience with education standards such as xAPI, LTI, or LMS plug-ins

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