AI Engineer-Agentic AI-Orchestration And Azure AI Foundry-Full‑Stack-Azure‑Native

patterns and structured scoring/assessment approaches where appropriate.

Agent Lifecycle Governance with Agent 365 (A365) Awareness (Core): Build solutions that align with enterprise lifecycle management and governance patterns such as:

•

• Agent registry / inventory expectations

• Access controls and telemetry/observability requirements

• Monitoring and operational controls at "agent scale

Runtime Security / Runtime Protection (Core): Implement and support

expectations for agentic solutions, and participate in controls aligned to:

•

• Runtime protection

• Access controls (e.g., Entra ID patterns)

• Threat detection and monitoring expectations

• This role is critical to ensuring the enterprise's AI ambition translates into

Core Software Engineering (Required)

• Strong hands-on development in

(or similar).

• Experience building API-driven services and integrating distributed systems. [Build agen...65 Copilot | SharePoint], [Agents in...65 Copilot | SharePoint]

• Strong understanding of

: reliability, availability, scalability, performance, and cost.

Azure & Platform Engineering

• Hands‑on experience with

for delivering enterprise GenAI solutions in an enterprise context.

• Experience building serverless and asynchronous workloads using

(including Durable Functions or equivalent).

• Experience using

for decoupled, reliable workflows.

• Experience working with

for data ingestion, storage, and processing.

• Experience using

as part of AI solutions.

Azure Functions + Queues/Eventing (Required)

• Experience with

(including Durable Functions or equivalent orchestration patterns).

• Experience implementing asynchronous patterns with

for scale and reliability.

Vector Databases (Required)

• Hands-on experience with

, including enterprise deployment patterns

LLM-as-a-Judge Evaluation (Required)

• Experience implementing evaluation approaches that include

(or equivalent automated evaluation patterns) for quality monitoring and continuous improvement.

Agent 365 (A365) + Governance Alignment (Required)

• Familiarity/experience working in environments using

-style lifecycle management concepts (e.g., agent registry, governance, monitoring/observability, and access controls)

Runtime Security / Runtime Protection (Required)

• Experience delivering solutions with

expectations (runtime security controls, access controls, and monitoring alignment as defined by enterprise governance).

Nice to Have

• Experience integrating AI services into enterprise automation platforms (e.g., Power Platform, ServiceNow).

• Familiarity with Azure AI services and data platforms.

AI & Agentic Solution Engineering

• Build and evolve AI applications and agents using Azure AI Foundry and Azure‑native services.

• Design and implement

and orchestration logic for complex use cases.

• Integrate AI capabilities into enterprise systems through

.

Full‑Stack & Backend Development

• Develop backend services, APIs, and supporting components for AI solutions.

• Build full‑stack solutions where required, including UI integration for AI experiences.

• Implement serverless components using Azure Functions for scalable, event‑driven execution.

Data, Retrieval & Knowledge Systems

• Design and implement data ingestion and storage pipelines using ADLS.

• Build and operate vector‑based retrieval systems for AI grounding and search.

• Maintain data freshness, indexing strategies, and retrieval performance.

Evaluation, Monitoring & Quality

• Implement evaluation pipelines for AI outputs, including

-based scoring and analysis.

• Instrument AI systems with logging, metrics, and telemetry to support observability and diagnostics.

• Use evaluation insights to improve accuracy, consistency, and system behavior over time.

Security, Governance & Operations

• Build AI systems aligned to

, including access controls and monitoring.

• Operate and support AI solutions in production, including incident response and root‑cause analysis.

• Continuously improve system reliability, performance, and cost efficiency.

Education:

• A degree in Computer Science / Engineering or a related discipline; or equivalent work experience

• 10+ years in a Global IT environment working with multiple disciplines to deliver projects in line with customer needs

• 3+ Years Global delivery or transformation preferably in large scale infrastructure programs

• 3+ Years in a global operations environment

• Python Certification

• Azure AI Services

• Azure Data Services