Artificial Intelligence Engineer

Senior AI Engineer
Location: Bangalore, India
Company: Care ADHD
Reports to: Director of Engineering
Role Overview
We are looking for a Senior AI Engineer to join our Bangalore engineering team and play
a leading role in how we design, build and safely deploy AI-powered capabilities across
the Care ADHD platform.
This is a senior, hands-on engineering role focused on taking AI from idea through to
production. You work with modern AI models and services, including Large Language
Models (LLMs), and build AI capabilities within our AWS-based technology platform.
You will be expected to take ownership of complex AI initiatives, working with Software
Engineers and QA Engineers in Bangalore alongside Product, Engineering and clinical
stakeholders in the UK. You will help turn sometimes ambiguous business and clinical
problems into well-designed technical solutions, determining where AI can deliver
genuine value and where more traditional approaches may be more appropriate.
As a senior member of the engineering team, you'll also help shape our approach to AI
engineering, establishing patterns and good practices that other engineers can follow
and sharing your knowledge across the wider engineering organisation.
Because we operate in healthcare, responsible AI is fundamental to the role. You'll
need to consider not only whether an AI solution can work, but how we can
demonstrate that it works reliably, safely and appropriately when dealing with sensitive
healthcare information (with ultimate responsibility for what is generated by AI).
Key Responsibilities
AI Product Development

Design, build and deploy AI-powered features across our patient, clinician and
internal platforms.
Build applications and workflows using Large Language Models and other
modern AI technologies.
Design and implement AI solutions using AWS services, including Amazon
Bedrock (Amazon Generative AI on AWS) and associated AWS capabilities.
Integrate foundation models and AI services into our existing Node.js/TypeScript
applications and services.
Develop solutions using techniques such as Retrieval-Augmented Generation
(RAG), structured outputs, tool use and agentic workflows.
Rapidly prototype and evaluate new AI capabilities before developing successful
approaches into production quality solutions.
Evaluate when AI is the right solution to a problem and when conventional
software engineering would potentially be more appropriate.
AI Engineering & Evaluation

Establish robust approaches for evaluating AI outputs for accuracy, reliability,
safety and usefulness. (Use of process such as Peer Reviewing to ensure
confidence)

Build automated and human in the loop evaluation processes.
Implement appropriate guardrails, monitoring and fallback behaviours for
production AI systems.
Understand and manage challenges including hallucination, model variability,
context management and prompt injection.

Monitor model performance, token usage, latency and cost in production.
Evaluate different models and approaches based on quality, performance,
security and cost.
Continuously assess emerging models, techniques and capabilities as AI
technology evolves.
Software Engineering & AWS

Build production-quality services and APIs supporting AI capabilities.
Integrate AI solutions with our wider Node.js/TypeScript, Next.js and AWS
technology stack.
Design solutions using appropriate AWS cloud-native services and architectural
patterns.

Write clean, maintainable and well-tested code.
Participate in code reviews and architectural discussions.
Contribute to automated testing, CI/CD pipeline improvements, Infrastructure
as Code (IaC) and observability.
Ensure AI capabilities form part of our wider engineering platform rather than
becoming isolated solutions.

AI Assisted Engineering

Champion the effective and responsible use of AI assisted software
development across Engineering.
Use tools such as Kiro (Amazon AI code agent) as part of day to day software
design and development.

Help establish good practices for spec. driven and AI assisted development.
Explore opportunities to use AI to improve developer productivity, quality and
engineering workflows.
Share knowledge and support other engineers in getting the most from AI
development tooling.

Security, Privacy & Responsible AI

Design AI solutions with security, privacy and patient safety at their core.
Ensure sensitive healthcare information is handled appropriately throughout AI
workflows.

Ensure solutions meet GDPR and relevant healthcare data protection
requirements.
Understand the security and privacy implications of foundation models and
third-party AI services.
Implement appropriate controls around data access, model inputs and outputs.
Contribute to engineering standards and governance for the responsible use of
AI.
Technical Leadership & Collaboration
Take technical ownership of AI initiatives from discovery and prototyping through
to production.
Help define architecture, patterns and engineering standards for AI across Care
ADHD.
Make pragmatic technical decisions around models, platforms, frameworks and
approaches.
Work closely with Product, Engineering and clinical stakeholders to identify
valuable applications of AI.
Provide technical guidance and mentoring to engineers working with AI
technologies.

Collaborate closely with engineering colleagues across Bangalore and the UK.
Communicate complex AI concepts clearly to both technical and non-technical
audiences.
Skills & Experience
Essential

Strong professional software engineering experience, operating at Senior
Engineer level.
Demonstrable experience delivering AI/LLM-powered capabilities into
production.

Strong development skills in Python and/or TypeScript.
Strong practical experience working with AWS and cloud-native architectures.
Experience integrating foundation models through APIs and SDKs.
Practical experience with prompt engineering, structured outputs and LLM
application design.

Experience with RAG, embeddings and context aware AI solutions.
Understanding of approaches for evaluating and monitoring AI generated
outputs.

Experience designing and building production APIs and distributed services.
Strong understanding of automated testing, Git (specifically GitHub, but not
essential) and CI/CD pipelines (GitHub Actions as part of that).
Understanding of security, privacy and data protection when building AI
systems.

Strong problem solving and debugging skills.
Excellent communication skills and experience working within distributed
engineering teams (Teams across UK and India).
Nice to Haves

Experience with Amazon Bedrock and the wider AWS AI/ML ecosystem.
Experience with Kiro or similar AI-assisted/specification-driven development
tools.

Experience with agentic AI systems and tool-based workflows.
Experience with LangChain (High level lib. for linear LLM workflows), LangGraph
(Orchestration runtime for complex, stateful multi agent loops), LlamaIndex
(Data ingestion, doc indexing and RAG) or equivalent technologies.
Experience with vector databases, embeddings and semantic search.
Experience with AI observability and evaluation platforms.
Experience with Infrastructure as Cod (AWS CloudFormation or similar such as
Terraform)

Knowledge of Machine Learning and Natural Language Processing beyond LLMs.
Experience within healthcare or another highly regulated environment.
Understanding of responsible AI, AI governance and emerging AI regulation.
What We Offer

The opportunity to build AI technology that can genuinely improve patient care.
The chance to influence how AI is adopted across a rapidly growing healthcare
technology organisation.
A modern AWS-based engineering environment with AI-assisted development at
the heart of how we work.
Collaboration with engineering, product and clinical teams across Bangalore
and the UK.

The opportunity to experiment with and evaluate emerging AI technologies.
A culture focused on engineering quality, experimentation and continuous
improvement.

Professional development and continuous learning.
Competitive salary and benefits.