Highlights
Experience with LLMs, vector search, and cloud-native deployment. Opportunity to work on enterprise-grade AI systems.
Description
Job Summary
pThe Junior AI Engineer will contribute to the development of enterprise-grade Generative AI systems and intelligent automation platforms. This role involves building Retrieval-Augmented Generation workflows, integrating Large Language Models into scalable applications, optimizing semantic search systems, and supporting cloud-native AI deployments.
Responsibilities
- Develop intelligent AI workflows powered by Large Language Models and retrieval-based architectures
- Build and maintain Retrieval-Augmented Generation pipelines using vector search and embedding technologies
- Create semantic search systems capable of delivering context-aware and accurate AI responses
- Design prompt engineering strategies for structured outputs, contextual grounding, and response optimization
- Configure inference workflows and optimize AI response generation performance
- Implement reasoning-oriented AI workflows using grounding methods and chain-based prompting techniques
- Support AI model enhancement activities through reinforcement learning concepts and tuning strategies
Required Skills
- Python Programming
- API Development
- Vector Search Technologies
- Semantic Search Systems
- Cloud-Native Deployment
Required Skills Explained
- Strong hands-on experience with Generative AI and LLM-powered application development.
- Knowledge of Retrieval-Augmented Generation workflows and vector-based information retrieval systems.
- Experience working with embeddings, semantic search, and contextual AI architectures.
- Understanding of prompt engineering techniques, grounding methods, and inference parameter optimization.
- Familiarity with reasoning-driven AI workflows and structured response generation approaches.
- Practical programming expertise in Python for AI and backend development.
- Experience building and integrating APIs for scalable AI services.
- Understanding of distributed application architecture and backend system design principles.
- Hands-on exposure to Google Cloud Platform services and cloud-native deployment workflows.
- Familiarity with GitHub, collaborative development practices, and repository management.
- Experience using Postman and Swagger for API testing and technical documentation.
- Strong analytical thinking, debugging ability, and problem-resolution skills.
- Ability to manage technically complex assignments with accountability and ownership.
- Good communication skills and collaborative mindset for cross-functional teamwork.
- Adaptability to evolving AI technologies, frameworks, and production requirements.
Who is this for
pThis role is ideal for candidates with a passion for AI, strong technical skills, and a keen interest in working on cutting-edge technologies. Experience with Generative AI and cloud platforms is essential.
Why This Job is a Good Opportunity
ulliThe opportunity to work on cutting-edge enterprise-grade Generative AI systems and intelligent automation platforms.liCollaboration with a dynamic team of engineers, data scientists, and other professionals in the field.liHands-on experience with advanced AI technologies like Large Language Models (LLMs) and vector search.liPotential to contribute to the development of innovative solutions that can significantly impact business operations.liThe chance to work on rapidly evolving AI projects in a production-focused environment, gaining valuable real-world experience.
Interview Preparation Tips
- Review and practice coding challenges and technical questions related to Python, API building, and distributed systems.
- Prepare examples of past projects where you have applied AI technologies or built scalable backend systems.
- Be ready to discuss your understanding of AI architectures, LLMs, and retrieval-based generation workflows.
- Bring a portfolio or samples that demonstrate your technical skills in areas like semantic search, embedding, and prompt engineering.
- Research the company's current AI projects and ask insightful questions during the interview to show your interest and enthusiasm.
Career Growth in This Role
pThe Junior AI Engineer role offers a clear pathway for career growth within the tech industry. As you gain experience, there are opportunities to take on more complex projects and leadership roles. You can advance to become an AI Lead or Principal Engineer, focusing on mentoring junior team members, leading cross-functional teams, and driving innovation in AI technologies.pThere is also potential for lateral movement into specialized areas like MLOps, data engineering, or cloud-native deployment practices. Additionally, this role provides a strong foundation for transitioning to product management roles where you can leverage your technical expertise to drive product development and strategy.
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Skills
Frequently Asked Questions
What qualifications are preferred for this role?Experience with vector databases, fine-tuning workflows, MLOps practices, and exposure to healthcare AI solutions is preferred.
Is remote work an option?This position requires onsite or hybrid work mode in Pune.
What technologies are used in this role?Key technologies include Python, PostgreSQL, Firestore, and Google Cloud Platform services.
