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At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

 

Senior AI Engineer (Gen AI and LLM Operations) 

 

As an AI & LLM Operations Engineer, you will sit at the intersection of software engineering, data engineering, and applied AI. You will design and operate agentic, multi‑agent systems that turn complex business workflows into reliable, production‑grade AI solutions. Partnering closely with engineering, data, and business stakeholders, you will integrate LLM‑powered capabilities into existing platforms, build conversational analytics over enterprise data, and ensure these systems are observable, secure, and scalable. This role is ideal if you bring a strong production and data engineering background and are eager to grow rapidly in AI/ML while shaping how next‑generation AI is built and operated.

 

YOUR TASKS AND RESPONSIBILITIES

 

The primary responsibilities of this role, AI & LLM Operations Engineer, are to:

  • Design and implement multi‑agent orchestration systems that coordinate AI agents across complex, multi‑step workflows (e.g., intake, planning, implementation, evaluation, supervision);
  • Build autonomous SDLC pipelines where AI agents support project intake, requirements refinement, GitHub issue creation, and code implementation with appropriate human oversight;
  • Integrate AI systems with existing engineering infrastructure, including GitHub, CI/CD pipelines, testing frameworks, and coding standards, to ensure seamless and secure operations;
  • Develop natural‑language query interfaces over complex enterprise data, combining structured and unstructured sources so business users can extract insights through conversation;
  • Build explainability, guardrails, and scope‑management layers to improve accuracy, handle edge cases gracefully, and increase trust in AI‑driven workflows;
  • Design and operate data and system architectures that enable reliable AI operations, including data integration layers, monitoring, logging, and incident response for AI services;
  • Collaborate with cross‑functional teams to understand business and data requirements, translate them into technical solutions, and iteratively deliver AI capabilities that drive measurable productivity gains.


WHO YOU ARE


Required Qualifications:

  • Strong programming skills in Python and experience building production‑grade systems and services;
  • Proven experience with CI/CD pipelines, GitHub workflows, version control practices, and modern SDLC and engineering best practices;
  • Deep understanding of production system operations, including monitoring, logging, debugging, incident response, and a focus on observability and reliability;
  • Solid foundation in data engineering, including data pipelines, SQL, and experience with both relational and NoSQL databases and processing data at scale;
  • Understanding of data quality, governance, and metadata management, with familiarity with data cataloging, lineage tracking, or knowledge management systems as a plus;
  • Experience with at least one major cloud platform (AWS, Azure, or GCP) and infrastructure‑as‑code, plus an understanding of security, governance, and compliance in data and AI systems;
  • Demonstrated production engineering mindset, with a track record of deploying and maintaining reliable systems and handling incident management or on‑call responsibilities;
  • Strong data and systems thinking, with the ability to design data flows and architectures that balance complexity with maintainability and support downstream applications;
  • Excellent written and verbal communication skills, including the ability to create documentation and technical specifications and to work effectively with engineering, product, and business teams;
  • High learning agility and adaptability, with a growth mindset, comfort with ambiguity, and self‑directed learning in AI/ML (e.g., side projects, courses, community involvement);
  • Active interest and hands‑on experimentation with LLMs and AI tools, with a basic understanding of prompt engineering, LLM capabilities and limitations, and curiosity about multi‑agent systems, RAG architectures, and emerging AI patterns.

Preferred Qualifications:

  • 5+ years of software engineering experience, including 3+ years focused on data engineering, data platforms, or analytics infrastructure;
  • Experience building data products that serve business users or analysts and familiarity with data warehousing concepts and platforms (e.g., Snowflake, BigQuery, Redshift);
  • Experience with workflow orchestration tools (e.g., Airflow, Prefect, Dagster) and background in search, recommendation systems, or information retrieval;
  • Exposure to AI/ML through side projects, hackathons, or proof‑of‑concepts, including experimentation with vector databases and semantic search technologies;
  • Prior experience building or contributing to LLM‑powered applications and familiarity with AI safety, responsible AI practices, and ethical AI considerations;
  • Knowledge of multi‑agent frameworks (e.g., LangGraph, AutoGen, CrewAI, or similar) and experience with developer experience, platform engineering, or internal tooling;
  • Background in analytics and measurement frameworks, contributions to open‑source projects or technical communities, and experience with change management or technology advocacy;
  • Prior work in highly regulated industries such as pharmaceuticals, finance, or healthcare.

 

What do We offer:

 

  • A flexible, hybrid work model
  • Great workplace in a new modern office in Warsaw
  • Career development, 360° Feedback & Mentoring programme
  • Wide access to professional development tools, trainings, & conferences
  • Company Bonus & Reward Structure
  • VIP Medical Care Package (including Dental & Mental health)
  • Holiday allowance ("Wczasy pod gruszą")
  • Life & Travel Insurance
  • Pension plan
  • Co-financed sport card - FitProfit
  • Meals Subsidy in Office
  • Additional days off
  • Budget for Home Office Setup & Maintenance
  • Access to Company Game Room equipped with table tennis, soccer table, Sony PlayStation 5 and Xbox Series X consoles setup with premium game passes, and massage chairs
  • Tailored-made support in relocation to Warsaw when needed
  • Please send your CV in English
  • You feel you do not meet all criteria we are looking for? That doesn't mean you aren't the right fit for the role. Apply with confidence, we value potential over perfection.
     

WORK LOCATION: WARSAW AL.JEROZOLIMSKIE 158

   
YOUR APPLICATION  
   

Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. 

Bayer offers the possibility of working in a hybrid model. We know how important work-life balance is, so our employees can work from home, from the office or combine both work environments. The possibilities of using the hybrid model are each time discussed with the manager.
Bayer respects and applies the Whistleblower Act in Poland.

 
   
   
Location: Warsaw   
Division: Crop Science  
Reference Code: 859444     

 

 

Location:

Warsaw

 

Division:

Crop Science

 

Reference Code:

859444 


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