Senior Backend Engineer - AI Platform
$121,500 per year
ApplySenior Backend Engineer - AI Platform
Posted yesterday
SENIORITY
Manager
SALARY
$121,500 per year
About the role
- Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution within Mobility platforms.
- Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.
- Implement and scale multi-agent architectures to support complex, distributed use cases across payments and fleet ecosystems.
- Integrate systems using Model Context Protocol (MCP) or similar frameworks to enable secure and scalable interaction between AI agents, APIs, and enterprise data sources.
- Build and optimize LLM-powered services (e.g., OpenAI APIs, LangChain) for production-grade performance, reliability, and cost efficiency.
- Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and compliance of AI-driven systems.
- Design solutions for context management, memory, and retrieval-augmented generation (RAG) to enhance agent effectiveness.
- Experience you'll bring
- Bachelors degree in Computer Science or Software Engineering 5-8 years of professional experience in software engineering
- Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills
- Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets
- Excellent written and verbal communication skills, and a collaborative and empathetic mindset
- Proficiency in backend development, with expertise in Java or C#, frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQLAgentic AI & MCP Experience
- Hands-on experience building or contributing to AI/LLM-powered applications or agent-based systems
- Familiarity with agent frameworks, tool-use patterns, and orchestration of LLM workflows
- Experience integrating AI systems with external tools/APIs using MCP or similar protocols
- Understanding of prompt engineering, embeddings, and vector-based retrieval systems
- Experience designing systems for scaling AI workloads in production environments
- Masters degree in computer science or software engineering 8+ years of experience in software engineering
- Experience with Python, Java, event-driven architecture and tools like Kafka
- Experience working on card payments
- Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes)
- Awareness of API security and PCI DSS compliance requirements
- Ability to work on existing codebase, contribute improvements, and adapt to legacy systems' constraints
- (AI Focus)
- Experience building AI skills & deploying AI solutions to production environments
- Experience building production-grade AI agents or copilots
- Familiarity with multi-agent systems and distributed AI architectures
- Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)
- Knowledge of AI evaluation techniques, safety practices, and responsible AI principles
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this
