AI Engineer
Spektr provides an AI-powered platform.
Funding history
Investors
About Spektr
Spektr offers a complete compliance operations platform combining AI agents and configurable processes. Its AI agents execute tasks such as KYB, document review, ownership mapping, source-of-funds analysis, website checks, and false-positive reduction, while connected workflows collect data, trigger checks, update records, and automate follow-up actions across onboarding, monitoring, risk, remediation, enrichment, questionnaires, and scoring. Spektr serves fintechs, enterprise banks, and other financial institutions, with case studies involving payments, crypto-wallet, digital banking, leasing, and EV-charging businesses.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the end-to-end AI roadmap, including model selection and product integration. You will design and deploy LLM-powered features, autonomous agents, RAG pipelines, and document-understanding capabilities. You will translate compliance problems into scalable AI solutions, evaluate model performance, research relevant AI advances, and make AI outputs accurate, explainable, and reliable.
Requirements
- 2+ years of experience in machine learning, AI, data, or backend roles
- Deep understanding of modern LLM stacks
- Strong TypeScript or Python skills
- Experience with LangChain or equivalent orchestration frameworks
- Experience building production-grade RAG pipelines
- Knowledge of embeddings, retrieval strategy, and re-ranking
- Experience with evaluation frameworks
- Experience deploying AI services in AWS or containerized environments
- Ability to communicate model architecture trade-offs and technical bottlenecks
Responsibilities
- Own the end-to-end AI roadmap and model integration
- Design and deploy LLM-powered features, autonomous agents, RAG pipelines, and document-understanding capabilities
- Translate compliance problems into scalable AI solutions
- Research AI and machine-learning papers and releases
- Build reliable, accurate, explainable, and hallucination-free AI outputs
Hiring Process
Intro call with the Talent team (30 minutes) → Technical Interview (30 minutes) → Technical Interview (60 minutes)