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Salary
≈ $36k – $95k per year (Estimated)
Location
Remote (Ukraine, PT hours)
Seniority
Senior
Employment
Full-Time

First seen by Alion on Oct 23, 2026. Luxoft scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Founded in 2000, Luxoft is a global digital strategy, custom software engineering, and IT consulting enterprise operating as a subsidiary of DXC Technology. Headquartered in Zug, Switzerland, the company serves multinational clients across key sectors including automotive, financial services, healthcare, media, and telecommunications. Through its bespoke software development, automated testing platforms, cloud architecture, and domain-tailored technology consulting, it enables enterprise organizations to accelerate digital transformation, optimize operational processes, and modernize mission-critical systems.

Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and Python services, PostgreSQL, Snowflake and AWS. We're looking for an applied AI engineer to build AI with real, measurable benefit across our operations and products.

Responsibilities:
Work closely with product teams to help define and execute technical criteria
Find high-value uses for AI and define how success is measured
Design, build and ship LLM-powered features and agents from prototype to production, such as automating client data onboarding
Own retrieval and RAG over our data, building on the foundation our data engineers prepare
Build evals and monitoring that track quality, cost and latency, and improve systems based on the results
Help refine our customer-facing AI features

Mandatory Skills Description:
Nearshore strongly preferred; otherwise at least 4 hours of daily overlap with US Pacific Time
Mid-to-senior software engineer who has shipped LLM-based features or agents to production, not only prototypes
Production experience in Python (preferred) or Node.js/TypeScript
Building with LLMs: prompt and tool design, structured outputs, retrieval/RAG and agent orchestration
Evaluating AI systems: eval sets built from representative data, automated graders, human review and production monitoring
AWS or another enterprise cloud platform, including its AI services (AWS Bedrock preferred)
AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CD
Strong English and communication skills

Nice-to-Have Skills Description:
Agent tool protocols such as MCP
SQL and cloud warehouse data (Snowflake preferred)
Infrastructure as code (e.g. Terraform)
Exposure to energy, utilities or sustainability data

Languages:English: B2 Upper Intermediate

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