Sr AI Architect​/Engineer

## Sr AI Architect/Engineer Apply:
USA
- Reston:
USA
- Virtual
- Kansas:
G
- Virtual
- South:
G
- Virtual
- North:
USA
- Virtual
- Illinois:
Full time:
Posted Today:
R3138

An extraordinarily talented group of individuals work together every day to drive TNS' success, from both professional and personal perspectives.  Come join the excellence!## ## Overview Researches, designs, plans, develops and/or evaluates new, advanced network technologies by translating customer requirements or strategic business objectives into final product design. Work typically includes in-depth assessment of the customer’s networked application needs, providing network modeling and simulation testing, consulting to further clarify needs, and engineering high-speed technology network transports to deliver application functionality.##

##
** Responsibilities**#
** Why this role exists
** TNS is moving from AI governance and foundations into execution. The platform building blocks are in place or underway — Microsoft 365, Copilot, Entra , SharePoint, and Anthropic's Claude models via AWS Bedrock. What we don't yet have is a dedicated person who can both
** build and operate the secure, production-grade AI platform that lets AI work safely against our data*
* * and
* ** embed with our lines of business to turn that capability into measurable value.
** This role does both. You'll be the technical engine and the on-the-ground partner who makes AI a productive, trusted tool across the enterprise — and who multiplies that impact by enabling others to build, not just building yourself.# #
** What you'll do
** Your time will span two connected halves.##
** Build and operate the AI platform
**** Model platform and private hosting.
** Own our Claude deployment on AWS Bedrock end to end — model access and versioning, region and data-residency decisions, provisioned throughput vs. on-demand, and the private, VPC-isolated hosting posture that keeps our data inside our boundary and out of third-party training. Evaluate and manage additional models where they fit, and maintain a routing layer so applications aren't hard-wired to a single model or provider.
** Harness and orchestration management.
** Build and maintain the application harness that sits between our users and the models: prompt and context management, tool and function calling, agent orchestration, retrieval pipelines, guardrails and content filtering, caching, and fallback behavior. Own the evaluation harness too — regression suites, quality benchmarks, and the release process that lets us upgrade models without breaking what's in production.
** Data connectivity.
** Design and build secure, governed connections between AI systems and TNS data — Microsoft 365 and Graph, SharePoint, databases, data warehouses, APIs, and line-of-business systems. Own the retrieval architecture, indexing and freshness strategy, and the permission-trimming that ensures every user sees only what they're entitled to see, with no leakage across boundaries.
** Security and access control.
** Architect least-privilege access across identity, network, and data layers — IAM and Entra , private networking, encryption and key management, secrets handling, and tenant isolation. Defend against AI-specific threats: prompt injection, data exfiltration through model outputs, insecure tool use, and over-permissioned agents. Partner with security and governance so every deployment is auditable and compliant by design, with a full audit trail of prompts, outputs, and data access.
** Monitoring and observability.
** Instrument the platform for production operations — latency, error rates, throughput and quota headroom, output quality and drift, guardrail trips, and anomalous usage. Build the dashboards and alerting that let us…