Job Description
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. The below job opportunity is to one of Our clients Who is a fashion specialty retailer founded on a simple idea: offer each customer the best possible service, quality, value, and selection. We are looking for an individual to provide specialized Information Technology support for our strategic business partners within the client Corporate Center.
Job Title: Engineer II, AI Agentic Solutions
Location: Seattle,WA 98101
Duration: 4 Months
Location: Seattle,WA 98101
Duration: 4 Months
Job Type: Temporary Assignment
Work Type: Onsite
Work Type: Onsite
Schedule: 08:00 AM - 05:00 PM PST
Job Description :
- As a Engineer 2, you are a lead individual contributor responsible for the quality of a team's work and capable of tackling complex design and problem solving without supervision.
- You are a product-minded engineer - you design systems spanning multiple weeks or months of work, hold a strong point of view on what good agent user experience looks like, make technical decisions that balance short and long-term business objectives, and take ownership of team-level costs and metrics.
- You will champion new techniques, mentor junior engineers, and be a key technical voice in cross-functional discussions.
A Day in the Life:
- Partner with business and technology stakeholders to define the "art of the possible" with agents - translating ambiguous problems into agentic solutions with clear success criteria and measurable outcomes.
- Design and build core agentic solutions end-to-end across orchestration, tool-use pipelines, and integration with enterprise systems.
- Own end-to-end solution design for agentic solutions spanning multiple engineers' work, with full upstream/downstream integration consideration.
- Apply context engineering to determine what an agent sees, when, and why - balancing token economics, latency, and decision quality across RAG patterns, structured retrieval, and dynamic prompt assembly.
- Develop and own evaluations and guardrails that demonstrate solutions are safe, reliable, and accurate - offline benchmarks, online production telemetry, and failure-mode analysis.
- Architect memory and state management approaches that let agents reason across sessions, users, and workflows - short-term context, long-term memory, and durable conversation state.
- Apply AI fluency to integrate LLM APIs, embedding models, vector stores, and agentic frameworks into production services; evaluate and adopt emerging techniques as appropriate.
- Make and clearly articulate technical trade-offs between short-term delivery needs and long-term scalability, factoring in design, framework choice, model selection, and infrastructure costs.
- Design systems accounting for current and upcoming product cycles, team-level cost responsibility, and alignment with cross-functional roadmaps.
- Lead design and code reviews across the team; provide actionable feedback and maintain a high bar for quality, testability, and extensibility.
- Design key metrics, evaluations, and observability patterns for agentic solutions; drive accountability for performance, cost, accuracy, and security of feature work.
- Work with business, infrastructure, and security teams to deliver enhancements, reliability improvements, and bug fixes for production AI systems.
- Surface potential design or delivery conflicts in the current or upcoming product cycle and make clear recommendations on the best path forward.
- Mentor and support junior engineers across a wide spectrum of technical activities; participate in hiring interviews with clear, specific feedback.
- Ensure own work and team members' work follows client's engineering and security standards; contribute to those standards
Required Skills:
- 6+ years of professional software engineering experience, with a strong track record of designing and delivering complex, scalable distributed systems.
- AI Fluency - Required: Hands-on experience working with LLMs, foundation model APIs (OpenAI, Anthropic, Google, etc.), prompt engineering, retrieval-augmented generation (RAG) architectures, and embedding-based search in production environments.
- Experience designing, building, and operating AI agents or agentic workflows in production, including tool-use, orchestration, and integration with downstream systems.
- Strong understanding of how to assemble, prune, and structure context for agents to maximize decision quality within token, latency, and cost constraints.
- Experience designing evaluation frameworks and safety guardrails for LLM-based systems, including offline benchmarks, online telemetry, and responsible deployment practices.
- Familiarity with short-term and long-term memory patterns for agents, vector stores, conversation state, and durable workflow state.
- Hands-on experience with agentic frameworks such as Claude Agent SDK, LangGraph, AutoGen, CrewAI, Semantic Kernel, or OpenAI Assistants API.
- Familiarity with multi-agent orchestration patterns: task decomposition, tool-use pipelines, and human-in-the-loop workflows.
- A product-minded approach to engineering: strong instincts for user impact, comfortable pushing back on requirements when the right solution isn't the one initially asked for, and able to translate business intent into agentic capabilities.
- Proficiency in Python; strong grasp of multiple tech stacks and cloud-native development on AWS and/or GCP.
- Experience working with cross-functional teams including product, business, infrastructure, and security stakeholders.
- Strong verbal and written communication skills; ability to articulate complex technical decisions to both technical and non-technical audiences.
- Agile development experience (Scrum, Kanban, Lean, or similar) with a continuous improvement and quality mindset.
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
Nice to Have:
- Experience with RESTful services, event-driven architectures, and backend databases (SQL, NoSQL, or cloud-native datastores).
- Familiarity with containerization technologies (Kubernetes, Docker) and modern CI/CD practices and tools (e.g., GitLab).
- Strong emphasis on building observability into systems - real-time alerting, dashboards, metrics, and performance accountability.
- Background in retail, e-commerce, or supply chain domains - understanding of how AI agents can drive value in inventory, fulfillment, personalization, or customer service.
- Experience with big data technologies (Spark, BigQuery, Redshift) and integrating ML models into production services.
- Contributions to open-source AI projects; curiosity and engagement with the broader AI/ML engineering community.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Numbers & Facts
| Location | Seattle, WA |
| Industry | Computer/IT Services |
| Salary | $60 |
| Company Size | 100 to 499 employees |
| Year Founded | 2009 |
| Website | http://www.tekwissen.com/ |
About Company
WE THE TEKWISSEN PEOPLE
TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.
To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.
Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.
It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.
Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.Skills
- Accountingunmatched
- Agile Programming Methodologiesunmatched
- Amazon Web Services (AWS)unmatched
- Application Programming Interface (API)unmatched
- Artificial Intelligence (AI)unmatched
- Artificial Intelligence (AI) Agentsunmatched
- Benchmarkingunmatched
- Big Dataunmatched
- Business Skillsunmatched
- Cloud Computingunmatched
- Code Reviewsunmatched
- Communication Skillsunmatched
- Computer Scienceunmatched
- Continuous Deployment/Deliveryunmatched
- Continuous Improvementunmatched
- Continuous Integrationunmatched
- Cross-Functionalunmatched
- Customer Support/Serviceunmatched
- Distributed Computingunmatched
- Diversityunmatched
- Dockerunmatched
- Economicsunmatched
- Engineeringunmatched
- Failure Analysisunmatched
- GCP (Good Clinical Practices)unmatched
- Kanbanunmatched
- Kernel Programmingunmatched
- Lean Manufacturingunmatched
- Memory Hardwareunmatched
- Memory Managementunmatched
- Mentoringunmatched
- Metricsunmatched
- NoSQLunmatched
- Open Sourceunmatched
- Performance Metricsunmatched
- Presentation/Verbal Skillsunmatched
- Problem Solving Skillsunmatched
- Product Engineeringunmatched
- Product Lifecycleunmatched
- Production Systemsunmatched
- Python Programming/Scripting Languageunmatched
- Quality Managementunmatched
- REST (Representational State Transfer)unmatched
- Reliability Engineeringunmatched
- Reporting Dashboardsunmatched
- Retailunmatched
- SQL (Structured Query Language)unmatched
- Scrum Project Management and Software Developmentunmatched
- Software Engineeringunmatched
- Supply Chainunmatched
- Systems Scalabilityunmatched
- Technical Supportunmatched
- Telemetryunmatched
- Testabilityunmatched
- User Interface/Experience (UI/UX)unmatched
- Workforce Managementunmatched
- Writing Skillsunmatched
- eCommerceunmatched
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