GenAI Engineer
Happiest Minds
Key Responsibilities
- As a GenAI Engineer at Happiest Minds, you will collaborate closely with the core AI division to fulfill the following metrics:
- Developing, structuring, and maintaining scalable AI-powered tools and backend services using Python.
- Assembling and integrating custom LLM-centric systems using state-of-the-art frameworks like LangChain.
- Formulating and fine-tuning advanced prompt engineering strategies to consistently optimize model outputs and precision.
- Creating, deploying, and optimizing robust, lightweight REST APIs using FastAPI or Flask architectures.
- Deploying structural vector databases and creating efficient Retrieval-Augmented Generation (RAG) pipelines to parse proprietary enterprise data safely.
- Integrating functional AI models securely with live web applications and distributed enterprise information software.
- Testing, analyzing, debugging, and systematically optimizing generative applications to drive speed and cost efficiency.
- Collaborating smoothly alongside senior software engineers, solution architects, product managers, and enterprise stakeholders.
- Staying continuously updated with rapid advancements, model drops, and tooling shifts across the global Generative AI and ML landscapes.
Skills & Eligibility
- Degree Track: Must hold or be completing a full-time B.E. / B.Tech degree.
- Specialization Fields: Computer Science, Information Technology, Artificial Intelligence, Data Science, or aligned engineering branches.
- Target Batch Alignment: Recent university graduates from the 2025 and 2026 pass-out batches are highly encouraged to submit applications.
- Programming Proficiency: Strong, unambiguous practical grasp of modern Python programming patterns and libraries.
- Generative AI Concepts: A solid baseline understanding of how Large Language Models (LLMs) operate and underlying GenAI concepts.
- Prompt Engineering: Conceptual clarity on constructing, optimizing, and evaluating effective prompts to guide model responses.
- API Architectures: Foundational knowledge of developing and mapping standard REST APIs.
- Version Control: Practical familiarity with Git version control pipelines and repository management.
- Soft Skills: Excellent structural analytical habits, strong logical troubleshooting qualities, clear communication skills, and a strong drive to learn.
- Hands-on developer exposure to orchestrating tools like LangChain, Langfuse , or equivalent AI development wrappers.
- Basic architectural awareness of Retrieval-Augmented Generation (RAG) concepts, embeddings, and modern Vector Databases (such as ChromaDB, Pinecone, etc.).
- Direct backend experience writing production-ready APIs via web frameworks like FastAPI or Flask .
- Familiarity with scaling applications on hyperscale cloud infrastructure environments (such as AWS, Microsoft Azure, or Google Cloud Platform).
- Completion of formal academic capstones, internships, or individual side-projects focusing explicitly on AI/ML or Generative AI.
- Verified certifications across Python developer tracks, foundational machine learning, or specialized LLM training courses.
- An active GitHub profile or public portfolio demonstrating functional code repositories and AI tool rollouts.
- Prior records of joining code hackathons or driving open-source project contributions.
- Degree Track: Must hold or be completing a full-time B.E. / B.Tech degree.
- Specialization Fields: Computer Science, Information Technology, Artificial Intelligence, Data Science, or aligned engineering branches.
- Target Batch Alignment: Recent university graduates from the 2025 and 2026 pass-out batches are highly encouraged to submit applications.
- Programming Proficiency: Strong, unambiguous practical grasp of modern Python programming patterns and libraries.
- Generative AI Concepts: A solid baseline understanding of how Large Language Models (LLMs) operate and underlying GenAI concepts.
- Prompt Engineering: Conceptual clarity on constructing, optimizing, and evaluating effective prompts to guide model responses.
- API Architectures: Foundational knowledge of developing and mapping standard REST APIs.
- Version Control: Practical familiarity with Git version control pipelines and repository management.
- Soft Skills: Excellent structural analytical habits, strong logical troubleshooting qualities, clear communication skills, and a strong drive to learn.
- Hands-on developer exposure to orchestrating tools like LangChain, Langfuse , or equivalent AI development wrappers.
- Basic architectural awareness of Retrieval-Augmented Generation (RAG) concepts, embeddings, and modern Vector Databases (such as ChromaDB, Pinecone, etc.).
- Direct backend experience writing production-ready APIs via web frameworks like FastAPI or Flask .
- Familiarity with scaling applications on hyperscale cloud infrastructure environments (such as AWS, Microsoft Azure, or Google Cloud Platform).
- The position accommodates early-career professionals ranging from 0 to 3 years of technical experience, making it perfect for both highly-skilled freshers and junior software engineers.
Note: This job is posted on external sites. Joblit shares the listing for convenience and does not take responsibility for third-party content.
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