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# Ai Engineer

- **Company:** TEKSYSTEMS INC.
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Salary:** $166,400.0 - $176,800.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Software Applications, Automated Storage and Retrieval Systems, Machine Learning, Systems Development Life Cycle, Software Engineering, Large Language Models, Multi-Agent Systems, Model Validation, Software Application Programming, AI Platforms, Kubernetes
- **Published:** August 28, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3367837050&tx=VT6257TTZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 5+ years of software engineering experience.
 * Hands-on experience building and deploying AI applications in production.
 * Strong understanding of LLMs, agentic workflows, prompt/context engineering, and modern AI architectures (in an enterprise capacity)
 * Experience developing AI agents from scratch and integrating external tools, APIs, and services.
 * Experience with agent frameworks, orchestration platforms, MCPs, skills, harnesses, or similar AI ecosystems.
 * Strong system design and architecture skills.
 * Ability to decompose complex business problems into scalable technical solutions.
 * Excellent communication and stakeholder management skills.
 * Demonstrated ability to work in ambiguous, fast-moving environments.

Preferred Qualifications

 * Experience with coding agents, AI-assisted software development, or SDLC automation.
 * Background in consulting, solution engineering, forward deployed engineering, or technical leadership roles
 * Exposure to model routing, RAG architectures, vector databases, and enterprise AI platforms.
 * Experience delivering customer-facing or business-facing AI solutions.
 * Prior experience working closely with product teams.
 * Alternate Profile: AI/ML Data Scientist

Additional Qualifications

 * Expertise in machine learning, predictive modeling, and statistical analysis.
 * Experience designing and deploying anomaly detection systems.
 * Strong Background in experimentation, model evaluation, and analytics.
 * Ability to identify opportunities where traditional ML approaches are more effective than agent-based solutions.
 * Experience partnering with engineers to operationalize AI/ML solutions in production environments., Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.

## Description

Join a newly formed, executive-sponsored AI Transformation team focused on bringing AI solutions from concept to production across a large enterprise environment. This team operates at the intersection of business and technology, partnering directly with stakeholders to identify high-impact opportunities, rapidly prototype solutions, and deliver AI-powered applications that drive measurable business outcomes.

This is an opportunity to work on greenfield AI initiatives, influence the future direction of enterprise AI adoption, and help establish best practices for how AI is implemented at scale.

What You'll Do

 * Partner directly with business stakeholders to understand challenges and identify AI-driven solutions.
 * Translate ambiguous business requirements into technical architectures and production-ready applications.
 * Design, develop, and deploy AI agents, copilots, and intelligent automation solutions.
 * Rapidly prototype and iterate on solutions to validate business value.
 * Build applications leveraging LLMs, agent frameworks, retrieval systems, and modern AI tooling.
 * Drive projects from ideation through deployment and adoption.
 * Collaborate with product, engineering, and program leadership to deliver measurable outcomes.
 * Advise stakeholders on AI capabilities, limitations, and implementation strategies.
 * Help define standards and best practices for enterprise AI development.


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