Senior AI Forward Deployed Software Engineer

New

ITFSAI software

Praca zdalna (Polska)ContractSenior

Salary250 - 400 PLN per hour

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Job Details

Languages: English: fluent, minimum C1, spoken and written.
Experience: Minimum 8 years of software engineering experience; minimum 2 years in customer-facing / embedded roles.
Required Skills: Node.jsPythonJavaAngularReactCI/CDLangChain

Have at least 8 years of software engineering experience.
Have at least 2 years of experience in customer-facing or embedded roles.
Have practical experience designing and implementing AI-native software and integrating AI into business and decision-making processes.
Be proficient in backend technologies including Python, Node.js, and Java.
Be proficient in frontend technologies including React and Angular.
Have practical knowledge of LLM tools and topics, including LangChain, Semantic Kernel, prompt chaining, vector search, and context management.
Have strong knowledge of system architecture, REST/GraphQL API design, and diagnosing and optimizing distributed-system performance.
Have DevOps experience and experience deploying solutions on AWS, Azure, or GCP.
Have experience with CI/CD, containers, and Infrastructure as Code.
Be willing to travel for business up to 30% of working time.
Have fluent spoken and written English at a minimum C1 level.

Design and implement production AI solutions end to end in agile iterations, covering backend services, data orchestration, LLM pipelines, and user interfaces.
Make architectural and application design decisions and ensure solutions are scalable.
Work with client teams in workshops to identify value streams and analyze business problems.
Build full-stack applications using REST/GraphQL APIs, data orchestration pipelines, vector database integrations, LangChain, Semantic Kernel, and React or Angular components.
Integrate with legacy systems and deliver implementations in a dynamic project environment.
Create reusable resources, libraries, SDKs, prompt templates, and documentation.
Share implementation findings with product teams and contribute to platform development.
Diagnose distributed systems, optimize latency, and implement monitoring and observability procedures.
Deploy and maintain cloud applications on AWS, Azure, or GCP using CI/CD, containerization, and Infrastructure as Code.
Lead technical implementations from the ground up and build working relationships with client architects, product managers, and teams.

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