Sr AI Developer

Responsibilities 70% – Hands‑On AI Development & Engineering

• Design, build, and deploy scalable AI/ML solutions (predictive models, generative AI, NLP, optimization, automation)
• Architect production-ready pipelines from data ingestion through model monitoring
• Develop and fine‑tune LLM-based applications (RAG architectures, prompt engineering, agents, copilots)
• Write high‑quality, production‑grade code (Python required; additional languages a plus)
• Implement MLOps best practices (CI/CD, model versioning, monitoring, drift detection)
• Work across cloud platforms (Azure, AWS, or GCP) to deploy secure, enterprise‑grade solutions
• Ensure governance, security, explainability, and responsible AI principles are embedded in every solution
• Optimize performance, scalability, and cost‑efficiency of AI workloads

• Translate ambiguous business problems into structured AI solution designs
• Partner with business stakeholders (Finance, Operations, Sales, Marketing, IT) to identify high‑value use cases
• Clearly explain AI concepts, tradeoffs, and model outputs to non‑technical audiences
• Lead solution design workshops and whiteboarding sessions
• Quantify expected ROI and define measurable success metrics
• Influence prioritization of AI initiatives based on business value and feasibility
• Mentor junior developers and help elevate AI literacy across the organization

• AI solutions deployed into production that generate measurable business impact
• Reduced time‑to‑value from idea to implementation
• Business leaders who trust and understand the AI solutions being delivered
• Scalable architecture that enables repeatable AI delivery across functions

• 7+ years of software development experience
• 3+ years building and deploying machine learning or AI solutions in production
• Strong proficiency in Python and ML frameworks (e.g., PyTorch, Tensor Flow, scikit‑learn)
• Experience with LLM ecosystems (OpenAI APIs, Hugging Face, Lang Chain, vector databases)
• Solid understanding of data engineering fundamentals
• Experience with cloud‑native AI deployment (Azure ML, AWS Sage Maker, Vertex AI, etc.)
• Ability to communicate complex technical ideas clearly and confidently
• Demonstrated experience working directly with business stakeholders

• Experience implementing enterprise‑scale AI governance frameworks
• Background in analytics, optimization, or decision intelligence
• Experience designing AI copilots or intelligent automation solutions
• MBA or strong business acumen
• Experience in regulated or complex operational environments

• Builder mindset with production discipline
• Systems thinker who designs for scale
• Commercially oriented technologist
• Comfortable in ambiguity
• Strong executive communication skills
• Bias for measurable outcomes over experimentation