Senior I AI Engineer

Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!

We're looking for a Senior AI Engineer to join our team and contribute to its continued growth.

As we're expecting to expand our team and launch new projects within the next 1-2 months, we're already accepting applications and starting the interview process for selected candidates. We'd love to hear from you - feel free to apply!

What the role does here:

• Builds and hardens an AI assistant grounded on a curated data layer;

• Delivers the product AI features: personalized recommendations, generated summaries and briefings, in-product assistance, learning suggestions, and detection of irregularities in reporting;

• Owns prompt and context orchestration, retrieving the right data from the catalog while respecting the requesting user permissions;

• Builds and maintains indexes for semantic search and keeps them current as the underlying tables change;

• Implements guardrails: resistance to instruction injection through user input and through retrieved data, hard limits on accessible scope, output filtering;

• Builds evaluation practice: example sets, regression runs when a model or prompt changes, and acceptance criteria;

• Monitors inputs, outputs, quality, latency and cost per request, and supports explainability of answers;

• Ships AI features into the service layer and the application interface.

Requirements:

• Python plus real production experience integrating large language models;

• Retrieval-augmented generation in practice: context assembly, relevance evaluation, working within context limits, vector indexes and keeping them fresh;

• Databricks as a context source: reading from the catalog, honouring grants and row-level rules when placing data into a prompt, platform vector search, and invoking models from SQL and jobs;

• Prompt and context engineering as a versioned, repeatable process;

• Evaluation of AI features: test sets, metrics, regression when the model updates;

• AI security: prompt injection, cross-tenant leakage, output filtering;

• FastAPI for the service side, and enough React to land a feature in the interface.

Nice to have:

• Publishing and monitoring models as endpoints on the platform, with a single access point that handles limits and cost;

• Azure OpenAI or another managed model service;

• Assistants in multi-tenant environments with hard data isolation;

• LLM observability: tracing, cost accounting, investigating answer-quality incidents;

• Shipping AI features to external users rather than internal staff only.

Softeq communicates only from @softeq.com email addresses. We never request payments or fees for any reason during hiring - including trainings or courses to be completed, equipment, onboarding, or background checks - and we will not ask for banking information, cryptocurrency or gift cards. If you receive a message from any other domain or requesting payment, do not respond and report it to [email protected]