Senior AI Engineer

About emerchantpay: emerchantpay is a leading global payment service provider and acquirer for online, mobile, in-store, and over-the-phone payments. Our enterprise global payments platform offers features including global acquiring, local alternative payment methods, advanced real-time fraud management, and transaction optimization engines, empowering businesses to design seamless financial consumer experiences.

Role Summary

We are seeking a Senior AI Engineer to join our core AI Engineering division as a senior individual contributor. In this role, you will help design, build, and deploy robust, production-grade AI solutions with a heavy emphasis on autonomous agents, tool-calling architectures, generative AI, and multi-tier LLM applications. Working closely alongside the AI Tech Lead, engineering squads, product teams, and cloud security architects, you will deliver resilient, data-driven AI models directly into live transaction systems.

Key Responsibilities

• Agentic Workflow Design: Design, build, and maintain production-grade AI agents that interact securely with internal APIs, multi-tenant databases, enterprise knowledge bases, and external tool frameworks.
• AWS AI/ML Implementation: Deploy advanced cloud-native architectures utilizing the comprehensive AWS ecosystem, focusing specifically on Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon SageMaker for inference orchestration, data monitoring, and safety model hosting.
• Advanced RAG Pipelines: Construct and scale end-to-end Retrieval-Augmented Generation (RAG) frameworks including customized document ingestion, chunking algorithms, embeddings vectors, semantic retrieval search, reranking, and model grounding.
• MLOps & Pipeline Engineering: Manage robust data preparation pipelines and MLOps practices covering model version management, hyperparameter tracking, model evaluation pipelines, containerization deployments, and continuous latency tracking.
• AI Evaluation & Guardrails: Define and implement quantitative evaluation metrics to monitor LLM outputs, assess hallucination parameters, govern prompt safety versioning, and setup enterprise-grade compliance guardrails.
• Cross-Functional Synergy: Partner with Product Managers, Data Scientists, DevOps teams, and Fintech Security divisions to transition experimental AI prototypes into scalable web services.

Required Skills & Qualifications

• 7–8 years of professional software development experience spanning AI engineering, Machine Learning pipelines, or data science tracks.
• 2–3 years of dedicated experience deploying machine learning models and LLM applications within high-availability live production environments.
• Robust experience building autonomous agentic workflows, multi-agent frameworks, tool-calling infrastructures, and orchestration patterns.
• Elite proficiency executing codebases using **Python** combined with microservice API frameworks (such as FastAPI, Flask, or Django).
• Familiarity incorporating frontend frameworks like React to design user-facing AI tools, testing dashboards, or internal analytics interfaces.
• Deep working mastery of cloud architectures using **AWS** (specifically Amazon Bedrock and SageMaker variants).
• Practical experience with advanced LLM orchestration libraries such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen .
• Familiarity with PyTorch, TensorFlow, Hugging Face Transformers, and standard vector databases (Amazon OpenSearch, Pinecone, pgvector).
• Knowledge of API management, microservices routing patterns, and event-driven architectures.
• Solid understanding of security governance for AI pipelines including access control vectors, encrypted secrets tracking, and strict data privacy compliance.
• Location Context: 100% remote working eligibility tailored for qualified technical professionals based within Sofia, Bulgaria .

Preferred Advantages

• Direct development experience using Amazon Bedrock Agents, Bedrock Knowledge Bases, and Bedrock Guardrails.
• Exposure to Docker containerization and orchestration architectures using AWS EKS or ECS.
• Experience managing Infrastructure as Code (IaC) templates via Terraform, AWS CDK, or CloudFormation.
• Prior domain engineering experience operating inside the Fintech or Global Payments industries.

What We Offer

• Fast-growing payment company infrastructure with state-of-the-art developer tooling.
• 100% remote-first operational setup backed by flexible working parameters.
• 25 days of baseline annual leave, expanding by 1 day for every 2 years of tenure.
• Comprehensive corporate support for continuing professional education, technical books, and advanced certifications.
• Regular collaborative team building events and structured social activities.