Senior AI Architect/Engineer

Transaction Network Services (TNS)

. Research, design, plan, develop, and evaluate advanced network technologies by translating customer requirements and strategic objectives into product designs .

Posted 10/13/2026full-timeRemote • United States, United Kingdom, BrazilSenior💰 $150,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production AI applications, with a strong focus on data governance, security, and cost management. Proficient in leveraging AWS Bedrock and related technologies to create scalable, secure AI solutions that drive business value.

Highest-signal resume keywords

AWS BedrockAI/LLM Application DevelopmentData GovernanceProduction OperationsEnterprise Security

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringModel DeploymentData ConnectivityEncryptionInfrastructure-as-CodeCI/CDMonitoringCost ManagementPrompt EngineeringEvaluation Harnesses

Soft Skills

Business FluencyCommunication SkillsBias Toward ShippingCollaboration

Tools & Technologies

AWS IAMAWS VPCAWS KMSAWS CloudWatchMicrosoft 365Azure AIPower PlatformEntra IDTerraformPrivateLink

Industry Keywords

Regulated IndustrySecurity-Sensitive IndustryPaymentsTelecomFinancial Data

Tech Stack

Tools & technologies

AWSAzureTerraform

About the role

Key responsibilities & impact

Research, design, plan, develop, and evaluate advanced network technologies by translating customer requirements and strategic objectives into product designs
Build and operate a secure, production-grade AI platform using AWS Bedrock
Own Claude deployment, model access and versioning, data residency, throughput, private VPC-isolated hosting, and model routing
Build and maintain application harnesses for prompt and context management, tool and function calling, agent orchestration, retrieval pipelines, guardrails, caching, and fallback behavior
Own evaluation harnesses, regression suites, quality benchmarks, and model release processes
Design secure, governed AI connections to Microsoft 365, Graph, SharePoint, databases, warehouses, APIs, and line-of-business systems
Own retrieval architecture, indexing, freshness, and permission trimming
Architect least-privilege identity, network, and data access using IAM, Entra ID, encryption, key management, secrets handling, and tenant isolation
Defend against prompt injection, data exfiltration, insecure tool use, and over-permissioned agents
Instrument monitoring and observability for latency, errors, throughput, quality, drift, guardrail trips, and anomalous usage
Manage AI costs through attribution, budgets, model right-sizing, caching, context optimization, batching, and throughput decisions
Create reusable patterns, templates, and guardrails for future AI use cases
Embed with Communications, Waypoint, Payments, and Corporate/Shared teams to identify AI and automation opportunities
Prototype, validate with users, ship production solutions, drive adoption, and measure business value
Enable AI champions across each line of business
Establish use-case intake and prioritization, cost transparency, and measurable first-year outcomes

Requirements

What you’ll need

Strong software / solutions engineering background with hands-on experience building and deploying production AI/LLM applications, including RAG, agents, tool use, orchestration, and evaluation
Direct experience with a managed model platform in production; AWS Bedrock strongly preferred, along with AWS IAM, VPC, KMS, CloudWatch, and PrivateLink
Demonstrated ability to build and operate data connectivity to enterprise systems with permission-aware retrieval
Working command of enterprise security and data governance, including identity and access, data protection, encryption and key management, and AI-specific threat models
Production operations experience, including monitoring and on-call ownership for live systems
Cost discipline and ability to attribute inference spend
Business fluency and communication skills for translating finance, operations, or sales problems into solutions
Demonstrated bias toward shipping and adoption rather than only building demos
Microsoft / Azure ecosystem experience, including Azure AI, Copilot Studio, Power Platform, Entra ID, and SharePoint / Graph (nice to have)
Experience in a regulated or security-sensitive industry such as payments, telecom, or financial data (nice to have)
Self-hosted or fine-tuned model experience (nice to have)
Infrastructure-as-code and CI/CD for AI systems, including Terraform, pipelines, and automated evaluations (nice to have)
Change-management or internal-consulting experience (nice to have)
Prior forward-deployed or customer-facing engineering experience (nice to have)

Benefits

Comp & perks

Medical coverage
Dental coverage
Life insurance
Paid holidays and vacations
401K plan with company match