This role is for a forward-thinking engineer passionate about applying artificial intelligence and automation to complex industry challenges. You will work directly with business units to uncover inefficiencies and translate real-world problems into technical solutions that drive measurable improvements in productivity and performance.
What You’ll Do
- Engage with stakeholders to assess operational gaps and define opportunities where AI and automation can create value.
- Perform feasibility studies to evaluate technical requirements, data availability, integration needs, and expected returns for proposed initiatives.
- Convert business needs into clear technical specifications, solution designs, and implementation roadmaps.
- Design and deploy AI-powered applications using natural language processing, computer vision, and generative AI models tailored to business use cases.
- Implement retrieval-augmented generation (RAG) systems, develop prompt engineering strategies, and build AI agent workflows to enhance automation capabilities.
- Develop and maintain robotic process automation (RPA) solutions using platforms like Power Automate or UiPath, along with custom scripting and low-code tools.
- Integrate disparate systems and data sources through APIs and workflow platforms to enable seamless end-to-end processes.
- Ensure data integrity for model training by building validation checks and monitoring pipelines.
- Document model decisions, lineage, and dependencies while continuously measuring performance against business goals.
- Write production-ready code following software engineering best practices, including modular design, version control with Git, code reviews, and automated testing.
- Follow a structured development lifecycle, from requirements gathering to deployment and ongoing optimization, within an agile environment.
- Collaborate with data scientists, engineers, and business teams to deliver integrated solutions that meet functional and operational needs.
- Advise internal teams on AI and automation technologies, promoting best practices and knowledge sharing across the organization.
- Stay current with advancements in AI/ML frameworks and tools, and apply emerging techniques to keep solutions innovative and effective.
- Support the operationalization of models and workflows in production, troubleshooting issues and refining performance over time.
- Champion reusability, scalability, and security in all developed systems, ensuring alignment with enterprise architecture standards.
- Mentor junior team members and contribute to a culture of continuous learning and improvement.
What We’re Looking For
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- At least 3 years of hands-on experience in AI/ML development, software engineering, or process automation.
- Proven track record building AI solutions involving NLP, computer vision, or generative AI.
- Experience with RPA tools (e.g., UiPath, Power Automate), scripting languages (Python, PowerShell), and workflow platforms.
- Strong programming skills in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Knowledge of prompt engineering, RAG architectures, and AI agent design patterns.
- Proficiency in API integration, data processing, and developing scalable software systems.
- Ability to turn business challenges into technical plans and deliver complete solutions from concept to deployment.
- Strong analytical mindset with a focus on delivering tangible business outcomes.
- Excellent communication skills, capable of conveying technical concepts clearly to non-technical audiences.
- Experience working in agile environments using Git, CI/CD pipelines, and collaborative development workflows.
- Ability to manage multiple projects and adjust priorities in a dynamic setting.
Preferred Qualifications
- Master’s degree in Computer Science, Data Science, or a related field.
- Background in power, energy, or industrial domains.
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies like Docker and Kubernetes.
- Experience with low-code/no-code development environments.
- Knowledge of MLOps practices and model deployment pipelines.
- Relevant certifications in AI, automation, or cloud technologies.
- Experience mentoring developers or leading technical initiatives.
Work Environment
This is a hybrid role with flexible work arrangements, allowing you to balance in-office collaboration with remote productivity. You’ll operate in a fast-paced, evolving environment where curiosity and resilience are valued, and where your contributions directly influence how the organization leverages technology to solve critical challenges.
