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Job Description

You will be responsible for designing, developing, and deploying robust and scalable AI Native Applications that leverage artificial intelligence (AI) and machine learning (ML) services and tools. You bring expertise in full-stack web application development using programing languages like Python and JavaScript frameworks such as Angular & React. You have demonstrated experience of fundamentals of machine learning principles, natural language processing (NLP) and principles of Generative AI. You must have experience on Google Cloud Platform (GCP) through the entire application life cycle management through development, deployment, telemetry, logging etc.,

Responsibilities:

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Design, develop, and maintain AI Native web applications and/or web services to deliver innovative features and functionalities. Eg: Retrival Augmented Generation

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Utilize Google Cloud Platform (GCP) services (e.g., AI Platform, Vertex AI, BigQuery, Cloud Storage) to build, train, and deploy AI Native Applications.

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Implement and integrate AI/ML models and ML Services into existing applications and systems using Python and JavaScript.

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Collaborate with data scientists, product managers, and other engineering teams to translate business requirements into technical solutions.

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Finetune models on GCP for use case specific needs.

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Conduct model evaluation, testing, and deployment, ensuring high-quality and reliable AI solutions.

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Stay updated with the latest advancements in AI, machine learning, and cloud technologies.

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Working knowledge of Agile Scrum methodologies including document technical designs, processes, and model specifications.

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Leverage LangChain, LangGraph, ADK, and other agent orchestration frameworks.

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Implement prompt engineering, chain-of-thought workflows, and retrieval-augmented generation (RAG) pipelines.

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Develop modular, scalable architectures for AI-powered web apps and APIs.

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Integrate LLMs with enterprise systems, databases, and external services.

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Implement vector databases for semantic search.

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Build connectors for structured/unstructured data ingestion.

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Work closely with automation teams, architects, and product owners to deliver end-to-end AI solutions.

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Document workflows and best practices for AI integration.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

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Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

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5+ years of experience as an AI Engineer, ML Engineer, or similar role.

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Strong proficiency in Python (mandatory) and familiarity with JavaScript/TypeScript.

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Hands-on experience with LangChain, ADK, and orchestration frameworks.

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Experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) and prompt engineering.

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Proficiency in GCP services and SDKs; experience with Azure or AWS is a plus.

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Strong knowledge of FastAPI/Django, Angular/React, and ML libraries (TensorFlow, PyTorch, scikit-learn).

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Familiarity with vector databases (Pinecone, Weaviate, FAISS).

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Experience with containerization (Docker/Kubernetes) and CI/CD pipelines.

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Good understanding of ML algorithms, deep learning, and statistical analysis.

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Ability to work independently and collaboratively in Agile environments.

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Excellent communication and interpersonal skills.