Developer – AI

About Infinova

Infinova is an emerging player in intelligent business transformation, dedicated to helping organizations scale smarter and achieve sustainable success. We are building a foundation that combines strategic consultancy, financial expertise, and technology-driven solutions to deliver measurable growth and operational efficiency.

Our services include AI-powered business consultancy, talent solutions, and advanced technology development, enabling businesses to convert data into actionable intelligence, optimize performance, and embrace innovation. With a commitment to transparency, quality, and future-ready strategies, Infinova ensures every partnership delivers lasting impact.

About the Role

The AI Developer will play a key role in designing, developing, and maintaining productiongrade AI and data workflows that power next-generation product capabilities. This role is hands-on and focused on building applications and pipelines that leverage LLMs, GenAI services, and cloud-native AI platforms—including Microsoft Fabric / Foundry, Azure, and AWS.

The ideal candidate is a self-starter who enjoys building real solutions, experimenting with modern AI tooling, and translating product requirements into working features. This role requires strong Python skills, experience with LLM / GenAI frameworks and APIs, and familiarity with cloud AI services. The successful candidate will be adaptable, collaborative, and motivated by delivering AI-driven outcomes that create measurable product impact.

Key Responsibilities

Design, develop, and maintain scalable AI and data workflows for production usecases, including ingestion, feature processing, and deployment of models and applications using Microsoft Fabric / Foundry, Azure Machine Learning, and AWS services such as S3, Glue, Lambda, Step Functions, and Bedrock.

Work directly with product teams and stakeholders to translate business requirements into AI-powered features, data flows, and solution designs that support measurable product outcomes.

Build and maintain automated validation, testing harnesses, and model / data quality checks, including unit tests, integration tests, A / B validations, and observability around model drift and performance.

Design, optimize, and refactor AI / ML pipelines, applications, and services for performance, reliability, and scalability using tools such as Synapse, Data Factory, Azure ML Pipelines, SageMaker, and serverless compute patterns.

Write production-quality code for AI workflows and supporting services, focusing on clean architecture, reusable components, and automation where appropriate.

Maintain technical documentation, architectural diagrams, and standards for AI pipelines, platform integrations, and reusable components.

Provide hands-on technical guidance, code reviews, and best-practice recommendations for other engineers, supporting a collaborative and innovative engineering culture.

Research, prototype, and implement emerging AI platform capabilities, e.g., model hosting, vector stores, feature stores, orchestration, and agent frameworks—within Microsoft Fabric / Foundry and AWS cloud environments.

Apply secure development practices, responsible AI principles, and data-protection policies to ensure compliance and protection of sensitive information.

Collaborate effectively with remote and cross-functional teams using modern development, version control, and communication tools.

SKILLS & EXPERIENCE

Bachelor’s degree in Computer Science, Engineering, or equivalent hands-on experience.

3–5+ years of experience in software engineering, AI / ML development, or building data-driven applications.

Practical experience working with LLM or GenAI frameworks and tooling (e.g., Azure / OpenAI APIs, Bedrock, LangChain, vector databases, prompt engineering techniques).

Proficiency with Python and modern data / AI libraries (e.g., Pandas, PySpark, FastAPI / Flask, embeddings frameworks, model evaluation tooling).

Experience with cloud AI services on Microsoft Fabric / Foundry, Azure, and / or AWS (e.g., Azure ML, Data Factory, Synapse, AWS Lambda, Step Functions, SageMaker, Bedrock).

Experience building production-ready AI features, pipelines, or applications including testing, monitoring, and quality checks.

Familiarity with product development practices and tools (JIRA, GitHub, Azure DevOps).

Understanding of modern data and AI concepts (vector representations, model finetuning, retrieval-augmented generation, data processing pipelines).

Ability to collaborate cross-functionally and translate product requirements into technical solutions.

Strong analytical and problem-solving skills, with the ability to operate independently in a cloud-based, distributed environment.