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This role is responsible for identifying, shaping, and delivering automation and AI solutions across key operational process areas in the Business Unit. The role partners directly with business leaders to understand pain points, evaluate workflow bottlenecks, and determine where advanced automation, machine learning, and intelligent orchestration can meaningfully improve speed, accuracy, and productivity.
Job Responsibility:
Assess business processes and identify opportunities where automation and AI can remove manual effort and improve productivity
Define technical architectures for automation and AI solutions, covering workflow orchestration, data needs, integrations, and model or rules-based components
Advise stakeholders on feasibility, solution options, and expected impact
convert business requirements into clear technical designs
Work hands-on with engineering teams to ensure solutions are built, tested, and deployed correctly, providing guidance during implementation
Evaluate emerging AI and automation technologies, run proofs-of-concept, and recommend adoption where they add value
Conduct design reviews to ensure consistency, quality, and adherence to architectural standards across projects
Mentor engineers and contribute to building reusable patterns, best practices, and long-term automation strategies
Prepare concise technical documentation and executive-level presentations that clearly explain solution design and business impact
Requirements:
Bachelor’s or master’s degree in computer science, engineering, data science, AI, or related quantitative field
Typically 10–15 years of experience in automation architecture, AI/ML engineering, or enterprise solution design
Strong understanding of applied AI concepts, including supervised/unsupervised learning, NLP, conversational AI, embeddings, vector search, and rules-based automation
Hands-on experience integrating ML models and AI services into production systems
familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, and modern LLM/agent tooling
Proficiency in Python and/or other engineering languages, with ability to produce maintainable code and automation logic
Experience designing data pipelines, performing data preparation, and ensuring data quality for automation and AI workloads
Demonstrated commitment to continuous learning and staying current with AI, automation, agentic frameworks, and orchestration technologies
Experience mentoring engineers, guiding design reviews, and influencing architectural decisions across teams
Strong communication skills for engaging stakeholders, explaining complex concepts, and aligning technical recommendations to business outcomes