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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformMicroservicesPythonSDLC
About the role
Key responsibilities & impact- Own end‑to‑end delivery of AI‑powered automation projects—from discovery to deployment, across various functional teams in Provation.
- Translate ambiguous business problems into concrete AI/ML opportunities.
- Build prototypes, minimum viable solutions (MVS), and demonstrable ROI models.
- Implement solutions using LLMs, agent frameworks, workflow automation, REST APIs, and cloud services.
- Collaborate with cross functional teams to scale or productionize successful pilots.
- Work directly with business stakeholders, SMEs, and process owners to identify high‑value AI opportunities.
- Coordinate with global engineering, data, and automation teams, including offshore centers.
- Create reusable templates, documentation, code modules, and training resources.
- Build playbooks and standardized modules that accelerate repeatable rollout across business units.
- Establish a repeatable “build → enable → transition → replicate” model for global AI adoption.
- Drive alignment with responsible AI, data governance, and enterprise engineering standards.
- Influence internal tooling, AI platform strategy, and long‑term architectural decisions.
Requirements
What you’ll need- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
- 4–7 years of hands‑on experience in software engineering, systems engineering, or automation development across diverse domains.
- Experience implementing AI/ML or automation solutions using Python, cloud platforms (AWS/Azure/GCP), REST APIs, microservices, GenAI APIs (OpenAI/Azure OpenAI/Bedrock), and workflow/orchestration tools.
- Familiarity with SDLC, DevOps, security, and compliance in enterprise environments.
- Strong communication and stakeholder engagement skills.
- Proven expertise in using Copliot CLI, Claude code to build applications rapidly.
- Ability to translate business needs into technical solutions.
- Proven ownership of end-to-end AI project lifecycle.
- Strong analytical and problem‑decomposition skills.
- Experience working with globally distributed/offshore teams.
- Ability to quickly learn enterprise tools and frameworks.
- Experience with intelligent automation for document processing, ticket triage, or reporting.
- Prompt engineering and LLM orchestration knowledge.
- Understanding of MLOps (nice‑to‑have).
- Experience in federated or shared-services environments.
Benefits
Comp & perks- Up to 25–30% travel
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AIMLautomationPythonREST APIsmicroservicesGenAI APIsworkflow toolsMLOpsintelligent automation
Soft Skills
communicationstakeholder engagementanalytical skillsproblem decompositioncollaborationinfluenceownershipadaptabilitylearning agilityproject management
Certifications
Bachelor's degreeMaster's degree