AI Software Engineer

TekWissen LLC
Dallas, TX, United States
about 1 month ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$176,800.0 - $197,600.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Abstraction Layers Application Programming Interfaces (APIs) Artificial Intelligence Software Applications Cloud Computing Software Debugging Fault Tolerance Monitoring of Systems Python (Programming Language) Open Source Technology Software Engineering
+18 more
Systems Integration Strategies of Testing Data Logging Performance Testing Large Language Models Multi-Agent Systems Backend Build Management AI Platforms Kubernetes Low Latency Production Code Performance Monitor Virtual Agents Terraform Serverless Computing Docker Microservices

Job description

  • Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuses on implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions., * AI Agent Engineering
  • Design and implement AI agents, including:
  • Retrieval (RAG)
  • Orchestration workflows
  • Tool/function invocation
  • Policy-based routing
  • Build evaluation frameworks for accuracy, latency, and reliability
  • Implement observability and monitoring for agent lifecycle

AI Platform Integration

  • Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)
  • Build abstraction layers to support multi-model and multi-provider architectures
  • Optimize model usage for performance, cost, and latency

Cloud-Native Development

  • Develop scalable services using:
  • Microservices architecture
  • Containers (Docker, Kubernetes)
  • Serverless and event-driven patterns
  • Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)
  • Ensure production readiness, logging, monitoring, and fault tolerance

Application Development

  • Build and deploy AI-powered applications aligned to business workflows
  • Integrate AI systems into existing enterprise platforms and APIs
  • Develop backend services and APIs supporting agent workflows

Testing & Performance

  • Define and execute test strategies for AI systems
  • Measure system performance (latency, throughput, accuracy, cost)
  • Debug and optimize production systems

Requirements

Do you have experience in System performance monitoring?, * 8-10+ years of software engineering experience

  • Strong experience with cloud-native systems (APIs, microservices, containers, serverless)
  • Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)
  • Proficiency in Python, Java, or similar backend languages

Experience with:

  • CI/CD pipelines
  • Infrastructure as code
  • Monitoring and observability tools
  • Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)

Preferred Experience

  • Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)
  • Experience designing multi-agent or distributed AI systems
  • Familiarity with enterprise-scale system integration
  • Experience optimizing AI workloads for cost and performance

Scope & Expectations

  • 100% hands-on engineering role (no people management)
  • Deliver production-quality code and deployments
  • Work within existing architecture and engineering standards
  • Collaborate with client and internal engineering teams as needed
  • Participate in technical design discussions (implementation-focused)

Benefits & conditions

3.83.8 out of 5 stars Dallas, TX 75376 $85 - $95 an hour - Temporary, Contract

About the company

TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

1:34 min

Essential commands for running and testing Terraform configurations

Hennie Francis · LIVE

3:31 min

Evolving developer roles into tech leads for AI agents

Alfonso Graziano Alfonso Graziano · Coffee With Developers

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

Videos

See all

Related articles

See all