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Senior AI Engineer

4 hours, 34 minutes ago
Bulgaria
Full-time
Senior
AI Engineer
Software Development
AWS AWS CDK CloudFormation CRM Django Docker ERP FastAPI Flask Generative AI LLM Machine Learning Microservices MLOps Python PyTorch React TensorFlow Terraform
Apply Now
emerchantpay

emerchantpay

emerchantpay specializes in providing seamless and secure online, mobile, and in-store payment processing solutions, along with risk and fraud management services, to help merchants enhance their conversion rates and expand their customer reach globally.

Diversified Financial Services
251-1K
Founded 2002
View All Jobs 10

Description

  • Design, build, and maintain AI-powered applications, services, and integrations.
  • Implement AI agents, agentic workflows, automation, and LLM-based business processes.
  • Develop AI applications using Python frameworks, React frontends, and modern AI/ML tooling.
  • Build solutions on AWS AI/ML services, including Amazon Bedrock, AgentCore, and SageMaker.
  • Collaborate with the AI Tech Lead on architecture, technology choices, engineering standards, and rollout approaches.
  • Provide technical guidance on AI implementation patterns, testing, observability, code quality, and production readiness.
  • Develop AI agents that interact safely with internal APIs, business workflows, enterprise systems, knowledge bases, and external tools.
  • Build and maintain RAG solutions, including ingestion, chunking, embeddings, retrieval, reranking, and grounding.
  • Support machine learning model development, deployment, monitoring, evaluation, and lifecycle management.
  • Integrate LLMs via APIs and implement evaluation approaches for output quality, safety, reliability, and hallucination detection.
  • Support prompt engineering, function calling, tool use, memory patterns, guardrails, and LLM application testing.
  • Collaborate with product, engineering, data, DevOps, security, and business stakeholders to deliver practical AI solutions.
  • Write clean, maintainable, testable, and well-documented code.
  • Support production rollouts, troubleshooting, monitoring, optimization, and continuous improvement of AI systems.

Requirements

  • 7-8 years of professional experience in software engineering, AI engineering, ML engineering, data science, or related technical roles.
  • 2-3 years of experience in AI development, ML engineering, or data science with production deployment experience.
  • Strong hands-on experience building production-grade AI, ML, and data-driven systems.
  • Practical experience with AI agents, agentic workflows, LLM-based applications, tool-calling architectures, workflow automation, and AI orchestration patterns.
  • Strong understanding of deep learning, generative AI, LLMs, embeddings, RAG, LLM fine-tuning, and AI evaluation.
  • Strong Python development experience, including FastAPI, Flask, Django, or equivalent frameworks.
  • Some experience with React for user-facing AI tools, internal applications, dashboards, or workflow interfaces.
  • Strong knowledge of AWS, including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker, and related AI/ML services.
  • Experience with agent/orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
  • Experience with PyTorch or TensorFlow, and familiarity with Hugging Face Transformers.
  • Hands-on experience using LLMs via APIs such as OpenAI, Anthropic, Gemini, or similar providers.
  • Experience with ML pipelines and MLOps, including training, deployment, tracking, monitoring, evaluation, and production support.
  • Experience with AI evaluation frameworks and techniques for LLM outputs, RAG quality, agent behavior, safety, and reliability.
  • Knowledge or practical experience with RLHF, human-in-the-loop evaluation, preference data, reward modeling, or feedback-driven improvement.
  • Experience with vector databases and retrieval/search technologies such as Amazon OpenSearch, Pinecone, or pgvector.
  • Experience building RAG systems, including document ingestion, embeddings, retrieval evaluation, reranking, and grounding.
  • Experience with model fine-tuning, embedding models, transformer architectures, open-source LLMs, and model benchmarking.
  • Knowledge of API design, microservices, event-driven systems, and cloud-based architectures.
  • Good understanding of security and governance requirements for AI systems, including access control, secrets management, data privacy, and audit logging.
  • Experience working in cross-functional teams with engineers, product managers, data scientists, DevOps, security, and business stakeholders.
  • Strong problem-solving skills and ability to turn prototypes into reliable production systems.
  • Strong communication skills for technical and non-technical stakeholders.
  • Experience with Amazon Bedrock Agents, Bedrock Knowledge Bases, or Bedrock Guardrails is an advantage.
  • Experience with Docker and EKS/ECS is an advantage.
  • Experience with Terraform, AWS CDK, or CloudFormation is an advantage.
  • Experience with data platforms, ETL/ELT pipelines, data lakes, feature stores, or real-time data processing is an advantage.
  • Experience implementing responsible AI controls, AI governance frameworks, safety guardrails, and compliance processes is an advantage.
  • Experience with observability for AI systems, including tracing, cost monitoring, prompt/model analytics, latency tracking, and quality dashboards is an advantage.
  • Experience integrating AI systems with enterprise platforms, CRM/ERP systems, ticketing systems, knowledge bases, and workflow engines is an advantage.
  • Contributions to open-source AI/ML projects, technical publications, conference talks, or patents are an advantage.
  • AWS certifications in architecture, machine learning, security, or DevOps are an advantage.
  • Experience in fintech is an advantage.

Benefits

  • Fast-growing payment company environment.
  • Excellent working conditions with a casual atmosphere and state-of-the-art hardware.
  • Modern, challenging, and constantly growing business.
  • Professional development support, including books, trainings, and certifications.
  • Team buildings and fun activities.
  • 25 days paid holiday, plus 1 additional day for every 2 years with the company.
  • Fully distributed and remote work.

Interested in this position?

Apply directly on the company website

Apply Now

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