Ai engineering lead

The role: Lead a compact AI engineering team hands-on:
Must have: Deep LLM integration, voice-pipeline (STT/TTS) and text-agent experience, Python, API design, Git Hub-based team workflow, production AI systems at scale, people leadership of small engineering teams.
Nice to have: Telephony platforms, collections or fintech domain, Azure, Kubernetes/Docker, CI/CD, Hugging Face ecosystem, eval frameworks.

Key Responsibilities:

Develop and implement AI Strategies aligned with business objectives. Establish AI engineering standards, governance and best practices Design develop and deploy AI, machine learning and generative AI solutions Oversee the end-to-end AI lifecycle from development to deployment and monitoring. Implement MLOps practices to support efficient model deployment and maintenance. Evaluate and adopt AI tools, frameworks and cloud technologies

Job Experience and skill required

Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or a related field. Masters (Preferred) 8+ years of software engineering or machine learning experience. 3+ years in a technical leadership or management role. Proven experience delivering enterprise-scale AI and machine learning solutions. Demonstrated experience working in cloud environments (Azure) Strong proficiency in Python and AI/ML frameworks such as Tensor Flow, Py Torch, Scikit-learn, and Lang Chain. Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents. Strong understanding of machine learning algorithms, NLP, deep learning, and data modeling. Familiarity with vector databases, API development, and microservices architecture.