Functional Lead delivering Salesforce Agentforce and AI implementation projects for NeuraFlash, an Accenture company. Managing customer relationships, project scope, financials, schedules, and delivery teams.
About the role
- Senior AI Platform Engineer building secure, production-grade Azure and Databricks AI platforms for AXIS Capital’s specialty insurance business. Developing LLM services, pipelines, APIs, and operational standards.
Responsibilities
- Design, build, and operate production-grade AI services, data pipelines, and platform capabilities on Azure and Databricks
- Develop LLM-powered and agentic workflows supporting business process automation, document intelligence, orchestration, and decision support
- Expose AI capabilities through secure, maintainable APIs and Azure Function or Container App backend services
- Own CI/CD delivery pipelines for AI and data workloads, including build, release, deployment, validation, and environment promotion
- Implement infrastructure-as-code using Terraform and Azure-native tooling
- Build and manage Databricks jobs, workflows, asset bundles, and data engineering pipelines
- Implement monitoring, logging, tracing, and alerting using OpenTelemetry or equivalent tools
- Support production AI systems through incident response, troubleshooting, operational runbooks, release readiness, and service improvement
- Contribute to architecture decisions, engineering standards, reusable patterns, and platform strategy
- Collaborate with engineering, data science, product, security, infrastructure, business, and vendor teams
- Mentor engineers, lead technical enablement sessions, and promote strong engineering practices
- Provide hands-on engineering delivery, standards, architecture, production support, and operational improvement
Requirements
- Strong production-level Python engineering experience
- Experience with PySpark or equivalent large-scale data processing frameworks
- Hands-on experience designing and operating CI/CD pipelines using Azure DevOps or similar tooling
- Experience deploying and supporting workloads on Azure, including identity, access control, networking, and secure resource configuration
- Practical experience with infrastructure-as-code, preferably Terraform
- Experience building APIs, backend services, and service integrations for data or AI workloads
- Experience with monitoring, logging, alerting, incident response, and operational support for production systems
- Strong engineering discipline across testing, code quality, branching, release management, and automated validation
- Ability to troubleshoot across application, data, infrastructure, deployment, and security boundaries
- Strong communication skills, with the ability to work with technical and non-technical stakeholders
- Experience with Databricks Jobs, Workflows, Asset Bundles, Apps, and medallion-style data architectures (desirable)
- Experience with Azure AI Foundry, Azure OpenAI, LLM-based application development, or agent SDKs and frameworks (desirable)
- Experience with MLflow, model lifecycle management, evaluation, tracing, and AI observability (desirable)
- Experience with containers, Docker, Kubernetes, AKS, OpenShift, or equivalent container platforms (desirable)
- Experience building reusable platform components, shared libraries, templates, or engineering standards (desirable)
- Experience working in regulated environments with strong security, governance, auditability, and operational control requirements (desirable)
- Ability to work independently, manage competing priorities, and provide clear technical leadership
- Ability to engage with stakeholders and explain technical decisions clearly
Benefits
- Inclusive and welcoming culture
- Equal employment opportunity regardless of protected characteristics
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
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