Job Description :

We are seeking an innovative and highly skilled AI Engineer with 4 - 9 years of experience in Artificial Intelligence, Machine Learning, and Generative AI technologies. The ideal candidate will be responsible for designing, developing, and deploying AI-powered solutions that address complex business challenges.

This role requires expertise in modern AI frameworks, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and cloud-based AI platforms. The candidate will work closely with business stakeholders, architects, and engineering teams to deliver scalable and impactful AI solutions.

Key Responsibilities :

- Design, develop, and deploy AI and Machine Learning solutions to solve business problems and improve operational efficiency.

- Collaborate with business stakeholders to understand requirements and translate them into AI-driven solutions.

- Lead solution architecture, technical design, and implementation of Generative AI applications.

- Develop and optimize AI workflows leveraging Large Language Models (LLMs) and foundation models.

- Build Retrieval-Augmented Generation (RAG) pipelines and intelligent knowledge retrieval systems.

- Design and implement Agentic AI solutions capable of autonomous reasoning, planning, and execution.

- Develop prompt engineering strategies to improve model accuracy, relevance, and response quality.

- Integrate AI models with enterprise applications, APIs, and business systems.

- Evaluate and deploy open-source and commercial LLMs based on business requirements.

- Work with vector databases and embedding models to enable semantic search and contextual retrieval.

- Develop multimodal AI applications involving text, image, audio, and document processing.

- Collaborate with data scientists, software engineers, and cloud teams to deploy scalable AI solutions.

- Monitor model performance, optimize inference costs, and ensure responsible AI practices.

- Stay current with emerging AI technologies, frameworks, and industry trends.

- Contribute to technical documentation, knowledge sharing, and AI best practices across the organization.

Required Skills & Experience :

- 6 - 10 years of experience in Software Engineering, Artificial Intelligence, Machine Learning, or Data Science.

- Strong hands-on experience developing AI and Machine Learning solutions.

- Proficiency in Python programming and modern software development practices.

- Experience in requirement gathering, solution design, architecture, and technical consulting.

- Strong understanding of Machine Learning concepts, model development, and deployment methodologies.

- Experience building enterprise-grade AI applications and intelligent automation solutions.

- Excellent analytical, problem-solving, and communication skills.

- Ability to work in a fast-paced, collaborative, and innovation-driven environment.

- Strong hands-on experience with Generative AI technologies and enterprise AI use cases.

- Experience with Prompt Engineering and LLM optimization techniques.

- Knowledge of Large Language Models including OpenAI, AWS Bedrock models, and Open-Source LLMs.

- Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

- Understanding of Vector Databases, Embeddings, Semantic Search, and Knowledge Retrieval systems.

- Experience integrating LLM APIs into enterprise applications.

- Familiarity with model evaluation, guardrails, AI governance, and responsible AI practices.

- Exposure to Agentic AI frameworks and autonomous AI systems.

- Experience with Advanced RAG architectures and contextual retrieval mechanisms.

- Knowledge of Multi-Agent systems and AI orchestration frameworks.

- Exposure to Multimodal AI applications involving text, image, audio, and document understanding.

- Understanding of AI workflow automation and intelligent decision-making systems.

- Hands-on experience with one or more of the following :

1. LangChain

2. LangGraph

3. AutoGen

4. CrewAI

5. Model Context Protocol (MCP)

6. Agent-to-Agent (A2A) Communication Frameworks

7. Prompt Management and AI Orchestration Frameworks

Cloud AI Platforms :

- Experience with one or more cloud-based AI platforms :

1. Google Cloud Vertex AI

2. Azure AI Foundry

3. AWS Bedrock

- Experience deploying, managing, and scaling AI workloads in cloud environments is highly desirable.

Preferred Skills :

- Exposure to low-code or no-code AI development platforms such as n8n, Microsoft Copilot Studio, or similar tools.

- Experience building AI-powered chatbots, assistants, copilots, and enterprise search solutions.

- Knowledge of MLOps, AI Operations, and model lifecycle management.

- Experience with API integrations and enterprise application development.

- Familiarity with data engineering and cloud-native architectures.

Preferred Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

- Relevant certifications in Azure AI, AWS AI/ML, Google Cloud AI, or Generative AI technologies.

- Contributions to AI research, open-source AI projects, or enterprise AI implementations will be an added advantage.