AI Native Software Engineer (Analyst / Senior Analyst) (Accenture Lithuania, UAB)
Darbdavys: Accenture Lithuania, UAB
Miestas: Vilnius
Paskelbta: 2026-11-01
Galioja iki: 2026-12-01
💶 1710–44700 €/mėn. Prieš mokesčius · full-time · iki 2026-12-01
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Job Description
Shape the Future of AI-Native Engineering
We're building the next generation of AI-native software engineers who use AI as a core part of how they build, test, and deliver software, not as an add-on.
As an AI Native Software Engineer (Analyst / Senior Analyst), you'll design, develop, and deploy production-grade software across the full stack while leveraging AI-assisted development tools as part of your everyday workflow. You'll work on real client projects across multiple industries, building applications that integrate with modern AI systems, including agentic architectures, LLM-powered solutions, and enterprise AI platforms.
This is not an entry point into AI, it's an opportunity to build a long-term career in one of the fastest-growing and most sought-after areas of technology.
What You'll Do
• Use AI coding assistants daily to accelerate software delivery and improve quality
• Design, build, and maintain modern full-stack applications
• Integrate Large Language Model (LLM) APIs into production applications
• Apply AI throughout the software development lifecycle, including testing, debugging, code reviews, and documentation
• Evaluate and validate AI-generated outputs to ensure quality, reliability, and security
• Define and track metrics that demonstrate the effectiveness of AI-assisted development
• Deliver solutions end-to-end, from design and development through deployment and production support
• Work closely with Agile teams and client stakeholders
• Develop APIs, interfaces, and application components that connect business applications with AI and agentic systems
• Contribute reusable components, engineering standards, and internal AI best practices
Requirements
• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related field
• Commercial software development experience, or equivalent experience gained through internships, academic programs, or personal projects
• Strong programming skills in at least one backend language: Python, Java, TypeScript
• Experience using AI tools as part of day-to-day software development
• Understanding of web development fundamentals, including JavaScript, HTML, and CSS
• Familiarity with cloud technologies (AWS, Azure, or GCP)
• Experience working with databases (SQL and/or NoSQL)
• Understanding of Agile delivery methodologies
• Awareness of software development best practices, CI/CD pipelines, and containerization technologies such as Docker
Nice to have
• Practical use of AI-assisted development tools to improve productivity and delivery outcomes
• Experience integrating LLM APIs into applications
• Understanding of token management, latency considerations, and cost optimization when working with AI services
• Ability to assess, refine, and improve AI-generated outputs
• Knowledge of AI limitations, risks, and responsible AI practices
• Familiarity with agentic systems, RAG architectures, LangChain, LangGraph, or similar frameworks
•…
Shape the Future of AI-Native Engineering
We're building the next generation of AI-native software engineers who use AI as a core part of how they build, test, and deliver software, not as an add-on.
As an AI Native Software Engineer (Analyst / Senior Analyst), you'll design, develop, and deploy production-grade software across the full stack while leveraging AI-assisted development tools as part of your everyday workflow. You'll work on real client projects across multiple industries, building applications that integrate with modern AI systems, including agentic architectures, LLM-powered solutions, and enterprise AI platforms.
This is not an entry point into AI, it's an opportunity to build a long-term career in one of the fastest-growing and most sought-after areas of technology.
What You'll Do
• Use AI coding assistants daily to accelerate software delivery and improve quality
• Design, build, and maintain modern full-stack applications
• Integrate Large Language Model (LLM) APIs into production applications
• Apply AI throughout the software development lifecycle, including testing, debugging, code reviews, and documentation
• Evaluate and validate AI-generated outputs to ensure quality, reliability, and security
• Define and track metrics that demonstrate the effectiveness of AI-assisted development
• Deliver solutions end-to-end, from design and development through deployment and production support
• Work closely with Agile teams and client stakeholders
• Develop APIs, interfaces, and application components that connect business applications with AI and agentic systems
• Contribute reusable components, engineering standards, and internal AI best practices
Requirements
• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related field
• Commercial software development experience, or equivalent experience gained through internships, academic programs, or personal projects
• Strong programming skills in at least one backend language: Python, Java, TypeScript
• Experience using AI tools as part of day-to-day software development
• Understanding of web development fundamentals, including JavaScript, HTML, and CSS
• Familiarity with cloud technologies (AWS, Azure, or GCP)
• Experience working with databases (SQL and/or NoSQL)
• Understanding of Agile delivery methodologies
• Awareness of software development best practices, CI/CD pipelines, and containerization technologies such as Docker
Nice to have
• Practical use of AI-assisted development tools to improve productivity and delivery outcomes
• Experience integrating LLM APIs into applications
• Understanding of token management, latency considerations, and cost optimization when working with AI services
• Ability to assess, refine, and improve AI-generated outputs
• Knowledge of AI limitations, risks, and responsible AI practices
• Familiarity with agentic systems, RAG architectures, LangChain, LangGraph, or similar frameworks
•…