Senior AI Engineer

About the Role :

Were looking for a Senior AI Engineer to design, build, and deploy Python-based agentic automations for simple-to-medium complexity business tasks, end-to-end from design through testing and deployment.

Some of this runs on GCP, so hands-on exposure to the platform is useful, though deep cloud expertise isnt the bar we care most about strong Python and agentic solution design skills.

From time to time youll also help convert an existing RPA automation into a Python-based agentic solution, but thats a small slice of the work the core of the role is building new automations.

Key Responsibilities :

• Design, develop, and deploy new Python-based automations and agentic workflows for simple-to-medium complexity business tasks, end-to-end from requirements through testing and deployment.

• Build and integrate agentic AI components (LLM-based agents, orchestration/tooling frameworks) into automations, choosing the right level of agentic-ness for the task at hand.

• Deploy and operate automations on Google Cloud Platform (GCP) where needed, integrating with APIs, databases, and enterprise systems.

• Write and execute automated unit and integration tests, and run these through CI/CD pipelines to ensure reliable deployments and mitigate production risk.

• Diagnose and resolve technical defects in your automations, optimizing performance and stabilizing processes before handoff to support teams.

• On occasion, assess an existing RPA/UiPath automation and convert it into a Python-based agentic solution a minor, occasional part of the role rather than the main focus.

• Act as a technical guide for junior and mid-level engineers within your pod; run peer code reviews to enforce coding standards and reusability.

• Serve as a technical representative in client meetings translating technical approach, trade-offs, and risk into language accessible to non-technical stakeholders.

• Collaborate with cross-functional stakeholders data engineers, DevOps, product managers, and business analysts to prioritize and deliver the automation roadmap.

• Stay current on industry trends in agentic AI and automation, and continuously improve our delivery methodology and service offerings.

Required Qualifications :

• 5+ years of hands-on Python software engineering experience, including building production services, APIs, and data pipelines.

• Experience building or integrating agentic AI automations (e.g., LLM-based agents, orchestration frameworks) for simple-to-medium complexity business tasks.

• Strong analytical and solution design skills able to take a business process description and design a clean, efficient Python/agentic automation for it.

• Experience with common Python data/engineering libraries (e.g., Pandas, NumPy) and building well-tested, maintainable code.

• Proficiency with containerization (Docker/Kubernetes) and CI/CD pipelines.

• Some hands-on exposure to Google Cloud Platform (GCP) e.g., Compute Engine, Cloud Run, Cloud Storage, or similar. Deep GCP expertise is not required; we're looking for enough familiarity to work in it and pick up more as needed.

• Strong track record operating in Agile/Scrum frameworks within enterprise engagements, working alongside BAs, developers, and business SMEs.

• Excellent communication and stakeholder management skills able to articulate technical challenges and solutions to both technical peers and project leadership.

• Cloud Deployment Experience : Deploy and manage Python-based applications and agentic solutions using Kubernetes, including GKE, and Google App Engine.

Nice to Have :

• Hands-on experience with UiPath (Studio, Orchestrator, REFramework) or other RPA platforms (Automation Anywhere, Power Automate) useful for the occasional RPA-to-agentic conversion.

• Exposure to UiPath AI Center / Action Center, Agentic AI solution design, or UiPath Advanced RPA Developer certification.

• Exposure to consulting environments or client-facing delivery roles.

• Familiarity with additional cloud platforms (AWS, Azure) beyond GCP.

• Interest in upskilling in adjacent technologies such as process mining (Celonis, UiPath Process Mining), low-code platforms (Power Apps), or conversational AI (Cognigy, Druid)