Confirmed on the employer's own hiring board on Oct 4, 2026. First seen by Alion on Oct 5, 2026. Itransition scores B on the Alion truth index.
Itransition has a new AI team that builds AI solutions for clients in any industry. Its projects range from adding AI to a system the client already runs to building a new product, and its work spans agents, assistants, and chat interfaces, as well as backend routing and optimisation, computer vision, and language model fine-tuning.
As a Senior AI/ML Engineer, you will be one of the first engineers on the team. You will take a project from the client's request to a production feature and lead 2-3 engineers on the project. In this role, the hard part is usually the data and the client's process, not the model. A project phase may end with evidence that the data cannot support the feature. That is a valid result when it comes early and explains why.
What is specific to this team:
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A new team: the first projects set how it works
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Direct contact with the client's managers and data
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A justified "this will not work" counts as a result, not a failure
If you are close but not across all of it, apply anyway and say where you are unsure.
Requirements
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Typically 5+ years in software or ML engineering; strong Python
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Knowing when a task needs AI and when plain code, a rule or a database query does it better
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LLM features and agents you took to production and kept running: function calling, RAG, agent workflows
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Agent frameworks: LangGraph, LlamaIndex or comparable
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Deployment to the cloud (Azure, AWS) and on premises, including local models
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Evaluation of LLM output: test sets agreed with the business, pass thresholds, error analysis
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Classical ML on tabular data: churn, segmentation, forecasting
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Planning the AI part of a project of 1 person-year or more, and leading 2-3 engineers on it
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Personal data and AI: GDPR, what may go to an external LLM provider and what may not
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Working English: you present results to the client's managers and defend a technical decision
Not expected: depth in every kind of AI work. Depth in LLM applications is the core; the rest you pick up on projects.
Responsibilities:
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Turn a client's request into a scope and an estimate: what data exists, what AI can do with it, what it costs
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Build a first version fast and check it on the client's real data
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Say early when the data cannot support a feature, and show why
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Take the feature to production and keep it running
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Lead 2-3 engineers and present results to the client's manager.
We offer:
- Projects for such clients as PayPal, Wargaming, Xerox, Philips, adidas and Toyota
- Competitive compensation that depends on your qualification and skills
- Career development system with clear skill qualifications
- Flexible working hours aligned to your schedule
- Options to work remotely
- Corporate medical insurance covering services of private and public medical centers
- English courses online
- Corporate parties and events for employees and their children
- Gym membership compensation, corporate sport competitions (cybersport included)
- 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate

