Senior GenAI Engineer

Full time

Yerevan

14 October 2026

Employment term Permanent

Category Other IT

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Job description:

The Senior GenAI Engineer is a core technical role within Ameriabank's formally established GenAI Enablement Service, operating under direct CIO sponsorship.

This role focuses on designing, building, and deploying AI-powered capabilities that serve as shared, reusable infrastructure for the entire bank - AI agent workflows, retrieval-augmented pipelines, enterprise knowledge systems, and integrations with the bank's internal technology ecosystem. All development is conducted in a secure, on-premise environment where data sovereignty and regulatory compliance are non-negotiable.

The Senior GenAI Engineer works at the intersection of applied AI engineering, enterprise systems integration, and responsible AI delivery - contributing directly to Ameriabank's AI Strategy priorities.

Job responsibilities

1. AI Solution Design & Development

Design, develop, and deploy AI-powered automations, agent workflows, and RAG pipelines serving multiple business domains across the bank
Design and evolve the Unified Enterprise Knowledge Base, including document ingestion, structured extraction, entity resolution, ontology/schema design, relationship extraction, evidence provenance, vector indexing, and hybrid GraphRAG retrieval.
Develop and maintain reusable AI components, agent templates, and reference architectures that any tribe or squad can build on - embodying the 'build once, enable many' principle
Design and implement Agentic AI frameworks - enabling autonomous multi-step workflows that coordinate across systems, tools, and processes

2. Integration & Enterprise Systems

Build and maintain integrations with enterprise systems - Jira, Confluence, TestRail, Azure DevOps - enabling AI-powered business and SDLC automation
Develop internal APIs and microservices connecting AI components with bank infrastructure
Integrate AI capabilities with the n8n (or similar) workflow automation platform - designing and maintaining production-grade AI-powered process automation pipelines
Contribute to the SDLC AI Agent System - an end-to-end AI-assisted software development lifecycle covering requirements analysis, test generation, code review, and documentation

3. Research, PoC & Experimentation

Lead proof-of-concept development for new AI technologies - multimodal models, voice and speech processing, vision models, and Agentic AI frameworks
Evaluate performance, accuracy, cost-efficiency, and security of models both in a controlled on-premise environment and in the cloud.
Research and assess emerging open-source models and tooling - recommending adoption decisions based on evidence from structured evaluation
Contribute to Armenian language model capability - evaluating multilingual models, fine-tuning approaches, and OCR solutions for Armenian document processing

4. Security, Governance & Documentation

Ensure all AI solutions adhere to the bank's data classification framework - determining appropriate deployment tier (local on-premise, cloud SaaS, or cloud PaaS) based on data sensitivity
Collaborate with Information Security, Cybersecurity, and Operational Risk to ensure secure data handling, audit trails, prompt management, and model transparency
Document AI architectures, pipelines, experiments, and design decisions - contributing to the reusable pattern library and knowledge base of the GenAI Enablement Service
Maintain the deployed AI capability registry - ensuring every production system has documented ownership, performance baselines, and governance records

Required qualifications

Experience: 5+ years in software engineering or applied AI/ML, with at least 2 years focused on GenAI systems in production environments
RAG & Knowledge Systems: Proven experience designing and maintaining RAG pipelines and vector databases.
Knowledge Graphs: Experience with graph data modeling, entity/relationship extraction, entity resolution, graph traversal and query languages such as Cypher. Experience combining graph and vector retrieval for GraphRAG is highly desirable.
Agentic Systems: Experience designing tool using LLM applications and multi-step AI workflows, including orchestration, state management, structured outputs, failure handling, human-in-the-loop controls and evaluation. Experience with LangGraph, LangChain, LlamaIndex or similar frameworks is desirable
Python & Software Engineering: Strong Python development skills, including testing, packaging, asynchronous programming, API development and production-quality software design
API & Integration: Solid API development experience and microservice architecture; experience integrating AI systems with enterprise platforms (Jira, Confluence, or similar)
Infrastructure: Containerization (Docker), Linux systems, and GPU-based local deployments; on-premise AI environment experience preferred
Automation: Experience with workflow automation platforms - n8n or similar - building production AI-powered process automation
Security: Understanding of data sensitivity classification, secure AI deployment practices, and compliance requirements in regulated environments

Additional information

Preferred Qualifications

Experience deploying and operating AI in secure, regulated industry environments - banking, financial services, or healthcare
Data engineering exposure - ETL pipelines, structured and unstructured data processing, SQL and Pandas proficiency
Experience collaborating within Agile or Agile@Scale delivery models
Contributions to open-source AI projects or internal innovation initiatives
Exposure to banking or financial services domain - understanding of core banking processes, regulatory environment, or financial data