Note: The job is a remote job and is open to candidates in USA. Anagh Technologies Inc is seeking a Senior Technical Manager to lead its Finance Technology AI Enablement engineering team. The role is responsible for setting technical strategy, leading AI/ML and GenAI solution delivery, enabling AI adoption, and overseeing multiple enterprise initiatives from ideation through production deployment.
Responsibilities
- Lead, mentor, and grow a high-performing engineering team focused on AI/ML and GenAI solution delivery
- Set strategic technical direction for the AI Enablement team, advocating for engineering best practices, scalable architecture, and responsible AI development
- Partner with business leaders and domain-specific IT teams to translate business requirements into actionable technical roadmaps and solutions
- Oversee end-to-end delivery of multiple concurrent AI initiatives, from ideation through production deployment and adoption
- Drive the design and development of AI/ML and GenAI solutions
- Champion the use of low-code/no-code platforms (e.g., Microsoft Copilot Studio, Power Automate) and Claude Skills alongside traditional full-stack development to accelerate solution delivery
- Establish and enforce DevOps, CI/CD, and data governance practices to ensure reliable, secure, and compliant delivery
- Operate within a regulated enterprise environment, ensuring solutions align with formal architecture, security, privacy, audit, and enterprise governance standards
- Act as a trusted advisor to business and IT partners on AI adoption strategy, use case evaluation, and solutioning
- Build and maintain strong cross-functional relationships, fostering collaboration between engineering, business, and governance stakeholders
- Report on program progress, risks, and value delivered to senior leadership
Skills
- 8+ years of people management experience, including building, leading, and developing high-performing engineering teams
- 5+ years of hands-on software development experience in cloud and distributed environments using modern technology stacks
- Demonstrated experience building AI/ML solutions, including exposure to GPT/Gemini/Claude LLM models, Vertex AI, RAG, GenAI, agentic AI workflows and orchestration
- Proficiency in Python and full-stack development, including designing and building APIs
- Hands-on experience with cloud platforms (Azure, GCP) and container orchestration using Kubernetes
- Experience working with vector databases in support of AI/ML and GenAI solutions
- Experience with major cloud AI/ML platforms (e.g., Google Cloud Vertex AI, Azure OpenAI, AWS Bedrock)
- Strong proficiency in SQL, data analytics, and automation
- Proven experience with DevOps practices and CI/CD pipelines
- Excellent communication and interpersonal skills, with a demonstrated ability to engage effectively with business leaders and translate business requirements into actionable technical plans
- Experience operating within a regulated enterprise environment, including familiarity with formal architecture, security, privacy, audit, and governance processes
- Strong strategic thinking and program management skills, with the ability to manage multiple concurrent initiatives in a fast-paced environment
- Bachelor or higher degree in Computer Science, Information Technology, or a related field, or equivalent practical experience
- Experience within Finance or a similar regulated financial services function
- Prior experience establishing or scaling an AI Enablement, AI Center of Excellence, or similar function
- Experience with agentic AI frameworks and orchestration tools
- Experience building and scaling low-code/no-code AI solutions (Copilot Studio agents, Power Automate flows, Claude Skills) as an enablement pattern for business and IT partners
- Experience designing or implementing semantic context layer using vector database and/or knowledge graph architectures to support GenAI and RAG solutions
- Familiarity with enterprise AI and Data governance, and responsible AI frameworks
- Experience presenting to and influencing executive-level stakeholders
- Track record of driving organizational change and technology adoption at scale
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