AI Architect

ECI is the leading global provider of managed services, cybersecurity, and business transformation for mid-market financial services organizations across the globe.  From its unmatched range of services, ECI provides stability, security and improved business performance, freeing clients from technology concerns and enabling them to focus on running their businesses.  More than 1,000 customers worldwide with over $3 trillion of assets under management put their trust in ECI. 

At ECI, we believe success is driven by passion and purpose. Our passion for technology is only surpassed by our commitment to empowering our employees around the world. 

The Opportunity: 

We are seeking an experienced AI Architect to define and guide secure, scalable, production-ready enterprise AI platforms and solutions for ECI clients. The role combines strategic architecture with hands-on technical leadership across generative AI, agentic AI, enterprise knowledge systems, governance, LLMOps, AI managed services, and presales solutioning. 

Client satisfaction is our top priority. This is a customer-facing role requiring excellent communication, collaboration, professionalism, and the ability to work effectively with business and technical stakeholders. 

At ECI, we are at the forefront of IT innovation, specializing in Data and AI services. This role will contribute to secure, scalable, governed, and reusable AI solutions for clients in highly regulated environments. 

This is an Hybrid role.

What you will do:

Lead discovery workshops and translate business, data, security, compliance, and operational requirements into enterprise AI architecture.

Lead discovery workshops and translate business, data, security, compliance, and operational requirements into enterprise AI architecture.

Define reusable reference architectures for generative AI, agentic AI, RAG, GraphRAG, knowledge platforms, and AI-enabled business workflows.

Own architecture decisions across Azure AI Foundry, Azure OpenAI, Copilot Studio, Microsoft Fabric, Azure AI Search, Power Platform, SharePoint, and related Azure services. 

Design multi-agent orchestration, tool-calling, Model Context Protocol (MCP), memory, reasoning, and human-in-the-loop patterns. 

Define AI governance, Responsible AI, security, identity, networking, data protection, content-safety, and approval guardrails in partnership with security and compliance teams. 

Establish LLMOps and AgentOps standards covering evaluation, prompt and model versioning, CI/CD, observability, tracing, release gates, rollback, and production support. 

Define managed-service operating models, including service boundaries, SLAs/SLOs, RACI, onboarding criteria, operational runbooks, incident processes, and continuous improvement. 

Lead technical presales, solution estimation, proposal development, architecture reviews, risk identification, and executive-level presentations. 

Guide engineering teams, review detailed designs, mentor technical leaders, and ensure solutions meet quality, scalability, resiliency, and cost objectives. 

Drive reusable intellectual property, accelerators, patterns, and lessons learned across ECI AI engagements

Who you are: 

7+ years of software, cloud, data, or solution architecture experience, including 2+ years designing and implementing generative AI solutions. 

Advanced experience with Python and API frameworks such as FastAPI or Django, plus strong understanding of REST APIs, asynchronous processing, and integration patterns. 

Demonstrated architecture experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, Copilot Studio, and adjacent Azure platform services. 

Experience designing production-grade RAG and agentic systems using frameworks such as Semantic Kernel, LangChain, LangGraph, or LlamaIndex. 

Practical knowledge of relational, document, graph, lakehouse, and vector data stores, including hybrid retrieval and metadata design. 

Experience defining cloud security, identity, private networking, secrets management, monitoring, resiliency, and disaster-recovery patterns. 

Ability to create architecture diagrams, HLDs, ADRs, technical roadmaps, estimation models, operating models, and customer-ready proposals. 

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field, or equivalent practical experience. 

Strong analytical, problem-solving, and critical-thinking skills with the ability to troubleshoot complex technical challenges. 

Excellent written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders. 

Experience working in Agile delivery environments using work-management and source-control tools such as Jira and GitHub. 

Working knowledge of secure software development, data privacy, responsible AI, and enterprise governance expectations. 

Technical Experience :

Enterprise AI architecture: conceptual, logical, deployment, integration, data, security, and operational architecture. 

Generative AI: prompt and context engineering, model selection and routing, grounding, structured output, tool use, fine-tuning decision criteria, and content safety. 

Agentic AI: multi-agent collaboration, planning and reasoning, MCP, memory, durable workflows, approval checkpoints, and autonomous-action boundaries. 

Knowledge systems: ingestion and enrichment pipelines, semantic and hybrid search, GraphRAG, knowledge graphs, taxonomy, chunking, ranking, citations, and access-aware retrieval. 

LLMOps and evaluation: offline and online evaluation, golden datasets, regression testing, red teaming, quality gates, telemetry, drift monitoring, and feedback loops. 

AI managed services: application inventory, risk and technical-debt assessment, onboarding, service transition, observability, incident response, KPI reporting, capacity planning, and continual optimization. 

AI FinOps: token and infrastructure cost monitoring, consumption forecasting, caching, model routing, performance tuning, and cost-to-value analysis. 

DevSecOps: Infrastructure as Code, CI/CD, environment strategy, policy-as-code, dependency security, release governance, and rollback patterns. 

Leadership: architecture governance, design reviews, technical mentoring, stakeholder alignment, delivery assurance, and technology roadmap ownership. 

ECI’s culture is all about connection - connection with our clients, our technology and most importantly with each other. In addition to working with an amazing team around the world, ECI also offers a competitive compensation package and so much more!  If you believe you would be a great fit and are ready for your best job ever, we would like to hear from you!   

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