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Lead I Software Engineering

  • Job type Posted on: Jul 23, 2026
  • Experience level TekWissen LLC
  • Employment type Bellevue, Washington
  • Remote status Salary: $126,880 per year
  • Employment type Onsite
  • Salary CTC
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Job Title :

Lead I Software Engineering

Job Type :

CTC

Job Location :

Bellevue Washington United States

Remote :

No

Jobcon Logo 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. Our client provider of digital technology and transformation, information technology and services
Position: Lead I - Software Engineering
Location: Bellevue, WA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite
Job Description:
Education & Experience:
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field - or equivalent practical experience demonstrated through a strong portfolio.
  • 0 2 years of professional experience, including internships, co-ops, or academic projects that demonstrate hands-on AI/ML or data engineering work.
  • At least one meaningful AI or ML project to point to - whether a course capstone, personal project, Kaggle competition, open source contribution, or internship deliverable.
AI / ML Foundations:
  • Working Python proficiency - comfortable writing scripts, functions, and classes; able to use libraries like pandas, NumPy, and scikit-learn for data manipulation and basic modeling.
  • Foundational understanding of machine learning concepts: supervised and unsupervised learning, classification, clustering, model evaluation, and overfitting.
  • Exposure to LLMs and generative AI - some hands-on experience prompting, fine-tuning, or building applications with foundation models (GPT, Claude, Gemini, Llama, or equivalent).
  • Basic familiarity with NLP concepts: tokenization, embeddings, semantic similarity, or text classification - through coursework or experimentation.
  • Curiosity about agentic AI frameworks (LangChain, LangGraph, or equivalent) and RAG architectures; hands-on experience is a strong plus but not required.
Data Skills:
  • Solid SQL proficiency - able to write queries to retrieve, filter, join, and aggregate data from relational databases.
  • Basic familiarity with data concepts: schemas, data types, relational databases, and cloud data storage patterns.
  • Exposure to Databricks, Azure, or cloud data platforms is a plus; willingness to learn these environments is required.
Engineering Practices:
  • Git-based version control experience and familiarity with collaborative development workflows.
  • Openness to code review and iterative improvement - comfortable receiving feedback and applying it.
  • Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE).
Soft Skills:
  • Genuine curiosity about AI and data - someone who experiments on their own time and follows developments in the field.
  • Strong problem-solving instincts - comfortable working with ambiguous problems and messy data.
  • Clear communicator - able to explain what you're building and why, both in writing and in conversation.
  • Growth mindset - energized by learning new domains, tools, and techniques quickly.
Must Have Skills:
  • Working Python proficiency for data manipulation, scripting, and AI/ML development
  • Foundational ML knowledge - able to explain core concepts and has applied them in at least one project
  • Exposure to LLMs or generative AI through hands-on experimentation, coursework, or project work
  • Basic NLP familiarity - embeddings, semantic similarity, or text classification concepts
  • Solid SQL proficiency for data retrieval and exploration
  • At least one AI/ML project portfolio piece to discuss (academic, personal, or professional)
  • Git-based version control experience
  • Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE)
Nice to Have:
  • Hands-on experience with LLM frameworks such as LangChain, LangGraph, or Google ADK
  • Experience building or experimenting with RAG pipelines including vector databases (Pinecone, FAISS, Weaviate, or equivalent)
  • Exposure to cloud platforms (Azure or AWS) for compute or storage
  • Familiarity with data governance concepts: data catalogs, business glossaries, data lineage, data quality, or metadata management
  • Experience with Databricks, Azure Data Factory, or DBT for data processing
  • Exposure to MLOps concepts: experiment tracking (MLflow, W&B), model versioning, or deployment pipelines
  • Familiarity with responsible AI concepts: bias, fairness, explainability, and AI safety
  • Relevant coursework or certifications: Databricks Generative AI Fundamentals, Azure AI Fundamentals (AI-900), DeepLearning.AI courses, or equivalent.
TekWissen Group is an equal opportunity employer supporting workforce diversity.

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Jobcon Logo Position Details

Posted:

Jul 23, 2026

Reference Number:

47634-12690

Employment:

CTC

Salary:

Not Available

City:

Bellevue

Job Origin:

CIEPAL_ORGANIC_FEED

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Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Position: Lead I - Software Engineering
Location: Bellevue, WA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite
Job Description:
Education & Experience:
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field - or equivalent practical experience demonstrated through a strong portfolio.
  • 0 2 years of professional experience, including internships, co-ops, or academic projects that demonstrate hands-on AI/ML or data engineering work.
  • At least one meaningful AI or ML project to point to - whether a course capstone, personal project, Kaggle competition, open source contribution, or internship deliverable.
AI / ML Foundations:
  • Working Python proficiency - comfortable writing scripts, functions, and classes; able to use libraries like pandas, NumPy, and scikit-learn for data manipulation and basic modeling.
  • Foundational understanding of machine learning concepts: supervised and unsupervised learning, classification, clustering, model evaluation, and overfitting.
  • Exposure to LLMs and generative AI - some hands-on experience prompting, fine-tuning, or building applications with foundation models (GPT, Claude, Gemini, Llama, or equivalent).
  • Basic familiarity with NLP concepts: tokenization, embeddings, semantic similarity, or text classification - through coursework or experimentation.
  • Curiosity about agentic AI frameworks (LangChain, LangGraph, or equivalent) and RAG architectures; hands-on experience is a strong plus but not required.
Data Skills:
  • Solid SQL proficiency - able to write queries to retrieve, filter, join, and aggregate data from relational databases.
  • Basic familiarity with data concepts: schemas, data types, relational databases, and cloud data storage patterns.
  • Exposure to Databricks, Azure, or cloud data platforms is a plus; willingness to learn these environments is required.
Engineering Practices:
  • Git-based version control experience and familiarity with collaborative development workflows.
  • Openness to code review and iterative improvement - comfortable receiving feedback and applying it.
  • Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE).
Soft Skills:
  • Genuine curiosity about AI and data - someone who experiments on their own time and follows developments in the field.
  • Strong problem-solving instincts - comfortable working with ambiguous problems and messy data.
  • Clear communicator - able to explain what you're building and why, both in writing and in conversation.
  • Growth mindset - energized by learning new domains, tools, and techniques quickly.
Must Have Skills:
  • Working Python proficiency for data manipulation, scripting, and AI/ML development
  • Foundational ML knowledge - able to explain core concepts and has applied them in at least one project
  • Exposure to LLMs or generative AI through hands-on experimentation, coursework, or project work
  • Basic NLP familiarity - embeddings, semantic similarity, or text classification concepts
  • Solid SQL proficiency for data retrieval and exploration
  • At least one AI/ML project portfolio piece to discuss (academic, personal, or professional)
  • Git-based version control experience
  • Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE)
Nice to Have:
  • Hands-on experience with LLM frameworks such as LangChain, LangGraph, or Google ADK
  • Experience building or experimenting with RAG pipelines including vector databases (Pinecone, FAISS, Weaviate, or equivalent)
  • Exposure to cloud platforms (Azure or AWS) for compute or storage
  • Familiarity with data governance concepts: data catalogs, business glossaries, data lineage, data quality, or metadata management
  • Experience with Databricks, Azure Data Factory, or DBT for data processing
  • Exposure to MLOps concepts: experiment tracking (MLflow, W&B), model versioning, or deployment pipelines
  • Familiarity with responsible AI concepts: bias, fairness, explainability, and AI safety
  • Relevant coursework or certifications: Databricks Generative AI Fundamentals, Azure AI Fundamentals (AI-900), DeepLearning.AI courses, or equivalent.
TekWissen Group is an equal opportunity employer supporting workforce diversity.

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