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Tech Stack
Tools & technologiesPythonPyTorchServiceNowTensorflow
About the role
Key responsibilities & impact- Build end-to-end AI agents and workflow automations from initial use-case scoping through deployment and ongoing maintenance.
- Write production Python code to integrate LLM APIs (prompt construction, response handling, context management, tool use) into internal workflows.
- Integrate AI tools with existing enterprise systems (NetSuite, HubSpot, M365, ServiceNow, etc.) via APIs with proper logging and monitoring.
- Establish reusable code patterns and component libraries to accelerate future agent development.
- Develop evaluation harnesses and model pipelines (training, evaluation, deployment) using AIOps practices to automate quality scoring and regression detection.
- Own deployed agent operations, including identity management, performance monitoring, human reinforcement workflows, and failure triaging.
- Optimize inference performance and cost through caching, batching, quantization, model selection, and workload management.
- Partner with Data Engineers to define feature requirements and create high-quality training and validation datasets.
- Apply responsible AI controls (privacy, security, governance) and collaborate with Security/Compliance to meet regulatory expectations.
- Maintain technical documentation, runbooks, and operational procedures for production AI services.
- Communicate project status, outcomes, and technical complexities clearly to both technical and non-technical stakeholders.
Requirements
What you’ll need- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent work experience.
- Proven experience (5+ years) building production software systems, with at least 2+ years delivering AI/ML or GenAI solutions.
- Strong software engineering fundamentals (APIs, testing, CI/CD, observability) and proficiency in Python and/or another relevant language.
- Experience with ML frameworks and tooling (e.g., PyTorch/TensorFlow-like concepts) and/or GenAI stacks (LLM APIs, vector databases, orchestration).
- Knowledge of AIOps practices (model registry, experiment tracking, deployment strategies, monitoring) and responsible AI principles.
- Ability to communicate clearly with both technical and non-technical stakeholders; comfortable iterating quickly in ambiguous problem spaces.
Benefits
Comp & perks- Competitive salary
- Flexible working hours
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
PythonAPIsAIOpsML frameworksGenAI solutionsmodel pipelinesproduction software systemstestingCI/CDobservability
Soft Skills
communicationproblem-solvingcollaborationadaptabilitystakeholder management