AI Applications Architect, AI Services

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation. At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.  We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.  We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.  Role Overview  The AI Applications Architect is the senior technical leader responsible for designing and delivering enterprise-grade architectures for agentic AI solutions across AHEAD’s client portfolio. This role defines the technical foundation for multi-agent systems, orchestrated workflows, retrieval infrastructure, and high-scale LLM integration within Kubernetes- and cloud-native environments.    This architect partners with Product Owners, engineering leads, and client stakeholders to translate strategic goals into scalable designs and implementation roadmaps. The role combines hands-on architectural design with engineering leadership, ensuring that solutions meet standards for reliability, security, observability, performance, and compliance.  Key Responsibilities

Architecture & Technical Leadership 

Design and own cloud-native architectures (AWS/Azure) for agentic AI workloads using Kubernetes/EKS, Terraform, Docker, serverless APIs, AWS Batch, and async orchestration frameworks (Celery, Step Functions, EventBridge, StoneBranch). 

Define agentic system patterns using LangChain, LangGraph, Autogen, LlamaIndex, Pinecone, and other multi-agent frameworks; ensure consistency of prompt/tool design, memory/state handling, and workflow orchestration. 

Architect vector database, RAG, embeddings pipelines, and model-serving endpoints (LLM/SLM) with strong emphasis on scalability and latency management. 

Establish platform-wide standards for API gateway patterns, identity and auth (OAuth2, Cognito, Vault), secrets management, event contracts/schemas, and data governance. 

Ensure holistic observability across multi-agent systems: tracing, metrics, logging, SLO/SLA definitions, synthetic checks, and incident response playbooks. 

Lead architecture reviews, threat modeling, and performance benchmarking for agentic workloads. 

Team Leadership & Technical Mentorship 

Guide engineering teams through architectural decisions, distributed design principles, and production-readiness standards. 

Mentor engineers in Kubernetes/EKS, async programming, multi-agent orchestration, cloud-native development, and responsible AI practices. 

Provide input on hiring, onboarding, and talent development to grow AHEAD’s agentic engineering bench. 

Delivery Excellence & Continuous Improvement 

Partner with Delivery Leads to ensure architecture is executable, scalable, and aligned with timelines. 

Champion automation, IaC, CI/CD, model deployment workflows, runbooks, and platform governance. 

Lead sprint-level architectural alignment, backlog refinement, retrospectives, and post-incident reviews. 

Stakeholder Engagement & Strategic Alignment 

Work with Product Owners and client stakeholders to shape roadmaps, define technical scope, and convert ambiguous problem statements into actionable designs. 

Communicate architectural decisions clearly to both technical and business audiences, balancing constraints, risks, and tradeoffs. 

Embed platform security, compliance, cost optimization, and data integrity into all architectural decisions. 

Qualifications

Required 

6+ years designing and delivering cloud-native, event-driven, or distributed architectures at scale (AWS/Azure). 

Deep hands-on experience with: 

Kubernetes/EKS, Docker, Terraform, and cloud infrastructure patterns 

Python, FastAPI, async frameworks, serverless APIs 

Vector DBs (Pinecone, Elasticsearch, pgvector) and RAG/LLM integration workflows 

Agentic AI frameworks (LangChain, LangGraph, Autogen, CrewAI, LlamaIndex) 

Strong knowledge of security, identity, devsecops pipelines, and secrets management in cloud environments. 

Proven leadership experience guiding engineering teams, performing code/design reviews, and enforcing architectural best practices. 

Excellent communication, stakeholder alignment, and documentation skills. 

Preferred 

Experience operating LLMs/SLMs in production (NIMs, Bedrock, OpenAI, Azure OpenAI). 

Experience with GPU clusters, inference optimization, or model-serving architectures (Ray, Triton, KServe). 

Consulting or client-facing architecture experience. 

 Success Metrics 

Delivery of resilient, scalable architectures for agentic solutions with measurable reliability and performance. 

Clear architectural guardrails and reusable patterns that accelerate delivery across teams. 

High engineering team engagement, skill growth, and adoption of architecture best practices. 

Positive client feedback, successful roadmap execution, and strong alignment to business outcomes. 

Contribution to AHEAD’s standing as the market leader in enterprise agentic AI engineering.