AI / Generative AI (Agentic AI) Expert

 Build POCs and production-ready solutions using LLMs, multimodal models, and agent frameworks.
• Evaluate, select, fine-tune, and optimize foundation models (open-source and commercial) based on use cases.
• Design and implement AI pipelines covering data ingestion, embeddings, RAG, agents, evaluation, and monitoring.
• Train, fine-tune, and adapt models using techniques such as prompt engineering, LoRA/PEFT, and fine-tuning.
• Integrate AI solutions with enterprise systems, APIs, tools, and backend platforms.
• Deploy and operate AI workloads across AWS, Azure, and GCP, leveraging native AI services where appropriate.
• Ensure scalability, reliability, security, and responsible AI practices in production environments.
• Collaborate with product, engineering, and platform teams to translate ideas into working AI systems.
 

All you need is...

AI / GenAI expertise
•    3+ years of hands-on experience in AI / ML, with strong focus on Generative AI and LLM-based systems.
•    Deep understanding of LLMs, embeddings, transformers, agentic patterns, and inference optimization.
•    Strong experience building Agentic AI systems (multi-step reasoning, tool calling, memory, orchestration).
•    Hands-on experience with model training, fine-tuning, and evaluation.
Core experience & SDLC
•    6+ years of overall software engineering experience, with strong exposure to SDLC, system design, and architecture.
•    Experience designing and delivering production-grade software systems, not just prototypes.
•    Strong understanding of software design principles, system integration, and scalable architectures.
Technical & platform skills
•    Proficiency in Python and experience with AI/ML frameworks and libraries.
•    Experience designing and deploying AI solutions on AWS, Azure, and/or GCP.
•    Strong understanding of API integration, backend systems, and cloud-native architectures.
•    Ability to independently drive POCs to production-grade solutions.
•    Strong problem-solving, communication, and technical leadership skills.

Preferred qualifications
•    Experience with RAG architectures, vector databases, and retrieval strategies.
•    Familiarity with LLMOps / MLOps, monitoring, and cost–performance optimization.
•    Exposure to open-source models and self-hosted inference stacks.
•    Experience building AI solutions for enterprise or platform-scale systems.

Nice to have
•    Working knowledge of Java and/or C#, especially in enterprise environments.
•    Exposure to legacy technologies (e.g., COBOL, JCL, batch systems) or legacy modernization initiatives.
•    Experience with multi-modal AI (text, vision, speech).
•    Understanding of responsible AI, governance, and security considerations.
•    Contributions to open-source, AI research, or internal AI platforms.