Mid-Level GenAI Engineer

About the Team:

Digital Transformation is all about Data Transformation and K2 is no different. Our Global Data Solutions team works fully remote and is formed by associates with diverse backgrounds and skills but who share a common mindset for analysis and problem-solving and strong work ethic of getting things done

We are also a multidisciplinary team focused and passionate about data. We are looking for someone who enjoys working with data science in general, and that has a team work spirit. We appreciate open and honest relationships (one of the crucial pillars of the company) and the communication as well.

• Build, deploy, and maintain GenAI-powered applications, including advanced chatbots and AI assistants using LLMs (think OpenAI, Azure OpenAI, Gemini, etc.).
  
  

• Work with modern GenAI frameworks like LangChain, LlamaIndex, Haystack, and similar to build RAG (Retrieval-Augmented Generation) and agent-based pipelines.
  
  

• Engineer data pipelines with Google Cloud, Airflow, and integrate structured and unstructured data sources for AI workloads.
  
  

• Leverage engineering copilots (e.g., GitHub Copilot, Cursor) to drive productivity, accelerate prototyping, and enforce best practices.
  
  

• Experiment with, benchmark, and fine-tune LLMs—prompt engineering, evaluation, vector search, and embedding optimization.
  
  

• Collaborate with data engineers and business stakeholders to deliver measurable results and insights.
  
  

• Apply business process understanding to design AI solutions that actually solve real problems, not just build for the sake of building.
  
  

• Analyze data, create ML models, and deliver actionable results.
  
  

• Document and share learnings with the team to raise the bar for everyone.
  
  

• Hands-on experience with LLMs or GenAI APIs: OpenAI, Azure OpenAI, Gemini, Anthropic, Cohere, or similar.
  
  

• Familiarity with GenAI frameworks: LangChain, LlamaIndex, Haystack, or similar toolkits.
  
  

• Proven ability to use engineering copilots like GitHub Copilot, Cursor, Cody, etc., to enhance development speed and code quality.
  
  

• Strong Python skills (must-have for all our AI/ML work).
  
  

• Experience with cloud platforms (Google Cloud preferred, but AWS/Azure also valuable).
  
  

• Solid understanding of machine learning and data modeling.
  
  

• Working knowledge of modern data engineering tools: Airflow, Pandas, SQL.
  
  

• Ability to operate as both an engineer and a data scientist.
  
  

• Knowledge of statistics and statistical analysis.
  
  

• Advanced English and strong communication skills (we work globally).
  
  

• Prompt engineering experience—building reusable prompt libraries, prompt tuning, or evaluation.
  
  

• Production-level RAG or agent-based GenAI system experience.
  
  

• Experience with Google Dialogflow or other conversational AI stacks.
  
  

• Exposure to vector databases (Pinecone, Weaviate, ChromaDB, pgvector, Milvus, etc.).
  
  

• Familiarity with MLOps or deploying ML models in production.
  
  

• BI tools experience (Looker, Tableau, PowerBI, etc.).
  
  

• Business acumen or consulting experience in AI/ML projects.
  
  

#LI-Hybrid

#LI-MB1

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This job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities at any time.

K2 Partnering Solutions is an equal employment opportunity/affirmative action employer. We do not discriminate on the basis of an individual's actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth and pregnancy-related conditions), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other characteristic protected by applicable federal, state, or local laws. Our team is dedicated to this policy with respect to all terms and conditions of employment, including recruitment, hiring, placement, promotion, transfer, training, compensation, benefits, employee activities, access to facilities and programs, and general treatment during employment.