AI Architect

Strategic Data Systems (SDS) has been a software consultancy firm specializing in strategy, technology, and business transformation for Fortune 100 companies, mid-sized firms, and startups. At SDS, we empower our development teams to address our clients' critical business challenges by leveraging cutting edge technologies. Join us today to work alongside fellow development specialists and become a crucial part of our dynamic and cohesive community.

Job Title: AI Architect

Location: Remote

Years of

Experience:

5‑8 YOE

Top

Skills:

software developer, cloud architect, AI capabilities

Soft Skills: Lead a team and work with stakeholders, coordinate to drive solutions. Strong leadership.

• This architect will focus on creating and architecting next‑gen innovation.
• Someone who can be productive with AI side of things. Architect with google, google agent stack, software development experience, CICD.
• We need someone with experience with AI and new technology.
• 50% hands on and 50% architect.

• Experience in cloud and distributed systems architecture focused on scalability, reliability, observability, and performance.
• Designing enterprise AI/ML systems; 1+ years hands‑on with GenAI, agentic workflows, RAG, LLM‑based integrations, or multi‑agent systems.
• Strong expertise with agentic frameworks and tooling (MCP, Lang Chain, Lang Graph, Llama Index, autogen, crewai, Agent SDK, OpenAI SDK, etc.).
• Hands‑on experience in modern software development and engineering practices.
• Proven experience integrating APIs and enterprise systems into agentic platforms and workflows.
• Ability to rapidly build AI‑driven prototypes, proofs of concept, and demo‑ready product experiences.
• Experience defining and governing enterprise architecture standards, patterns, and reference architectures.
• Deep understanding of MCP servers, tool calling, registries, eval pipelines, agent observability, and multi‑agent orchestration.
• Hands‑on experience with Azure and GCP, including Kubernetes, containerization, identity, networking, CI/CD, and API platforms.
• Familiarity with AIOps/MLOps stacks (MLflow, model registries, vector DBs, semantic layers, feature stores, monitoring).
• Strong knowledge of security, compliance, risk, and Responsible AI (RAI) considerations for enterprise agent systems.
• Demonstrated ability to partner across engineering, data science, product, and security teams to deliver complex AI platform architectures.
• Define and evolve the enterprise reference architecture for AI agents, including orchestration frameworks, tool integration patterns, MCP servers, registries, and multi‑agent coordination.
• Design large‑scale agent orchestration platforms that enable autonomous workflows across commerce, operations, and internal productivity domains.
• Responsible for operational uptime adhering to SLAs, planning upgrades, rolling out new capabilities and integrations for agent platform.
• Establish grounding patterns using semantic layers, vector search, knowledge models, and Retrieval‑Augmented Generation (RAG).
• Architect and develop systems that connect agents to trusted enterprise data, APIs, and business services.
• Develop architectural patterns for safe, governed agent execution aligned with Responsible AI principles.
• Architect scalable, fault‑tolerant AI agent platforms across hybrid cloud environments (Azure & GCP).
• Establish architecture standards ensuring low latency, high availability, resiliency, and observability.
• Partner with cloud and platform engineering teams to deliver containerized, API‑driven, secure infrastructure for agent workloads.
• Define platform lifecycle patterns including versioning, release gating, rollback strategies, and performance benchmarking.
• Enable cost‑efficient scaling of AI workloads across millions of enterprise and customer interactions.
• Define, develop and operationalize the Agentic SDLC, including evaluation frameworks, safety testing, regression gates, and release readiness criteria.
• Architect systems for continuous agent improvement using automated evaluation pipelines and human feedback loops.
• Establish enterprise standards for hallucination mitigation, prompt safety, PII protection, and AI misuse prevention.
• Lead…