Note: The job is a remote job and is open to candidates in USA. Systems Engineering Services Corporation (SESC) is seeking a highly experienced Senior AI Platform Engineer to build and operate secure, governed enterprise AI infrastructure. The role focuses initially on BYOK-based AI coding-agent platforms using Azure AI Foundry and AWS Bedrock, then expands to AI gateways, MCP integrations, observability, AI FinOps, governance, and reusable agent-development platforms.
Responsibilities
- Develop unified telemetry for AI platforms, including model calls, tool calls, data access, latency, errors, token consumption, cost, policy decisions, and team/user attribution
- Establish dashboards and reporting for AI usage and financial management
- Track:
- Token consumption
- Model and API usage
- Cost attribution
- Budget thresholds
- Anomalies
- Adoption trends
- Forecast versus actual spend
- Showback/chargeback
- Develop AI evaluation and quality-control processes, including test harnesses, regression testing, red-team scenarios, hallucination/failure detection, and release gates
- Establish production SLOs, monitoring, alerting, runbooks, incident response, root-cause analysis, and continuous platform hardening
- Create developer onboarding guides, sample applications, approved model-selection guidance, and training materials
- Develop reusable reference architectures for:
- Coding-agent workflows
- Secure prompt and data handling
- Repository access
- Pull request/code review workflows
- Tool-use guardrails
- Partner with Enterprise Architecture, Cloud Engineering, Security, SRE, Developer Productivity, Legal/Risk, and application engineering teams
- Establish engineering standards for AI agents, BYOK, MCP, gateway policies, observability, and secure AI development
Skills
- Strong hands-on Python development experience
- Strong infrastructure-as-code experience with Terraform, Bicep, CloudFormation, or equivalent
- Experience with containers, Kubernetes and/or serverless architectures
- Strong understanding of CI/CD, secrets management, private networking, and enterprise identity
- Hands-on experience with: • Azure AI Foundry • Azure API Management • Azure Monitor / Application Insights • Microsoft Entra ID • Azure Key Vault • Azure Private Link • Azure Policy
- Working knowledge of: • AWS Bedrock • AWS GovCloud • AWS IAM • CloudWatch • AWS networking • Multi-cloud/cross-cloud architectures
- Experience designing or operating LLM gateways, model-routing layers, API gateways, MCP servers/gateways, tool/function calling, RAG pipelines, or agent orchestration platforms
- Experience administering or governing GitHub Copilot SaaS, including access management, licensing, policy configuration, and usage reporting
- Strong security architecture knowledge, including: • Least privilege • RBAC/ABAC • Conditional access • Encryption • Egress controls • Audit logging • Data classification • Secrets management
- Understanding of regulated cloud environments and frameworks such as NIST, CMMC, FedRAMP, FISMA, and CUI requirements
- Experience implementing observability for distributed systems, including logs, metrics, traces, dashboards, alerts, SLOs, incident response, and operational runbooks
- Excellent communication skills with the ability to explain technical architecture, security risk, cost, compliance, and operational trade-offs to both technical and non-technical stakeholders
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Azure AI Engineer Associate
- Microsoft Azure Security Engineer Associate
- AWS Certified Solutions Architect
- AWS Security Specialty
- AWS Machine Learning certification
- GitHub Copilot, GitHub Actions, or GitHub Advanced Security certification
- FinOps Certified Practitioner
- Terraform or Kubernetes certification
- CISSP
- CCSP
- CompTIA Security+
- Comparable cloud, AI, security, platform, or FinOps certifications
- Experience with GitHub Copilot Enterprise, GitHub Copilot BYOK, Claude Code, Anthropic SDKs, OpenAI/Azure OpenAI APIs, or AWS Bedrock
- Experience with MCP, A2A, LangGraph, Semantic Kernel, LlamaIndex, LangChain, AWS AgentCore, or similar AI orchestration frameworks
- Experience developing AI gateways with: • Model allow-lists • Content safety • Prompt-injection defenses • Usage metering • Model routing • Rate limiting • Circuit breakers • Cost attribution
- Experience with Microsoft Purview, Defender for Cloud, Microsoft Sentinel/SIEM, policy-as-code, OpenTelemetry, Langfuse, Arize, LangSmith, or similar AI observability/evaluation technologies
- Experience supporting the Defense Industrial Base (DIB), Federal environments, GCC High, Azure Government, AWS GovCloud, or CUI workloads
- Experience implementing cloud or AI showback/chargeback models
- Experience with AI FinOps, cloud cost management, token economics, cost allocation, budget controls, forecasting, anomaly detection, and financial reporting
- Experience owning enterprise platform roadmaps, operating models, onboarding processes, SLOs, runbooks, and stakeholder communications
Benefits
- Group medical, dental, vision, life, long-term disability, and short-term disability insurance
- 21 days of accrued paid time off
- 401(k)
- Tuition reimbursement
- Performance bonuses
- Paid overtime
Company Overview
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