AI Engineer

About the Role

We are looking for talented engineers who combine strong communication, stakeholder management, and hands‑on expertise in AI agents. You should be equally comfortable presenting a solution to a Fortune 500 business sponsor, working through ambiguous requirements with product managers, and building production‑grade agentic workflows in code. A sense of ownership, continuous learning, and genuine curiosity about the rapidly evolving agent ecosystem are essential.

At Flexday AI, you will design, build, and deploy production‑grade Agentic AI solutions for large enterprise clients. We are a multi‑cloud (AWS, Azure, GCP) and multi‑LLM (OpenAI, Azure OpenAI, Anthropic, Gemini) AI solutions firm, and you will work with global teams across the full development lifecycle, from discovery to production.

• Partner with client stakeholders, product owners, and business leads to understand requirements, shape solutions, and communicate progress clearly and credibly
• Design and develop Agentic AI solutions deployed at enterprise scale
• Translate functional and business requirements into technical solutions in collaboration with product and business teams
• Build, test, and deploy AI components on AWS, Azure, or GCP
• Take end‑to‑end ownership of features, from development through production
• Collaborate with remote, cross‑functional global teams across multiple time zones

• Excellent written and verbal communication skills in English
• Demonstrated ability to explain technical concepts to non‑technical business stakeholders
• Comfort facilitating working sessions, leading solution walkthroughs, and managing expectations with client sponsors
• Strong sense of ownership, accountability, and follow‑through
• Ability to operate independently in ambiguous, fast‑moving environments

• Solid working knowledge of AI agents, agentic workflows, and the patterns behind them, such as tool use, planning, memory, and multi‑agent orchestration
• Hands‑on experience building agents using frameworks such as Lang Graph, Lang Chain, OpenAI Agents SDK, Semantic Kernel, or equivalent (professional or personal projects both count)
• Understanding of how to evaluate, debug, and product ionize agent behavior in enterprise settings
• Familiarity with Model Context Protocol (MCP) servers and multi‑agent orchestration patterns is strongly preferred

• LLM and Generative AI: prompt engineering, RAG, fine‑tuning, and LLM integration
• Machine Learning: classical ML, feature engineering, model training, evaluation, and deployment
• Computer Vision: CNNs, detection, segmentation, vision transformers, or OCR

• 2 to 5+ years of hands‑on software development experience, primarily in Python
• Proven contribution to large‑scale programs deployed in enterprise environments
• Understanding of full‑stack development, REST APIs, and microservices
• Disciplined approach to code quality, testing, and documentation

• Hands‑on experience developing and deploying on AWS or Azure (GCP is a plus)
• Experience working with large datasets and data pipelines
• Familiarity with Docker and Git

• Amazon Bedrock and Amazon Bedrock Agent Core
• Microsoft Copilot and Copilot Studio

• Lang Graph, Lang Chain, OpenAI Agents SDK, or similar
• Model Context Protocol (MCP) servers and multi‑agent orchestration

• Vector databases (Pinecone, Weaviate, Qdrant, pgvector)
• Embedding pipelines, semantic search, and document intelligence
• Databricks, PySpark, Microsoft Fabric, Synapse, or similar platforms, with a good working understanding of the underlying concepts

• Understanding of CI/CD, model deployment, monitoring, and observability
• Hands‑on experience with any industry‑leading MLOps tools and platforms

• Bachelor’s or Master’s degree in computer science, Engineering, Data Science, or a related technical field from a reputed institution.
• A PhD or equivalent qualification is highly valued, and candidates with doctoral backgrounds are encouraged to apply