דרושים » הנדסה » Software Engineer -AI Backend

Requirements:
Technical Expertise:
Programming: Advanced proficiency in Python for backend development and AI applications
GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.)
Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures
Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques
Cloud Platforms:
Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS)
Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.)
Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services
Software Engineering: Strong background in microservices architecture, API development, and production system design
AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques
Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration
OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing
Data Pipelines (Advantage): Experience building and maintaining data processing pipelines
Professional Experience
Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience
Production Systems: Proven track record of deploying and maintaining AI solutions in production environments
Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions
Education & Background
Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field
Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio)
Soft Skills
Problem-Solving: Excellent analytical and creative problem-solving abilities
Communication: Strong technical communication skills for both technical and non-technical audiences
Collaboration: Proven ability to work effectively in cross-functional teams
Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies
Consulting Mindset: Ability to understand client needs and provide strategic technical guidance.

Requirements:
Must Have
1+ years of software development experience
Strong proficiency in Python for backend development
Experience building backend systems (APIs, databases, or services)
Solid understanding of data science fundamentals statistics, ML concepts, and working with data pipelines
Familiarity with at least one major cloud platform (GCP, Azure, or AWS)
Understanding of software engineering principles and architecture basics
Familiarity with GenAI / LLM concepts
Bachelor's degree in Computer Science, Data Science, or related field or equivalent practical experience
Advantages
Experience with LLM provider APIs (OpenAI, Anthropic, Google)
Exposure to multi-agent systems or LLM-based workflows
Hands-on experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)
Academic research or projects in AI, NLP, or data science
Personal or university projects involving multi-agent systems or ML model development
Docker and Kubernetes experience
Experience working on production systems in a client-facing environment.

Requirements:
Excellent coding skills in Python/TypeScript, with at least 5 years of hands-on experience building reliable backend services, agents and tooling. Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) is a strong advantage.
Experience designing, deploying, and maintaining production systems that integrate ML components, including APIs, microservices, model serving layers, feature pipelines, monitoring, and CI/CD/MLOps workflows.
Solid experience with AI related contexts Understanding of prompt engineering and LLM optimization techniques, RAG architecture
Solid understanding of distributed systems concepts, performance optimization, observability, and operating services at scale.
Strong communication skills, with the ability to bridge technical, product, and business perspectives.
Prior experience in cybersecurity, fraud prevention, or identity management is a plus, especially with secure system architectures or ML-augmented decisioning systems.
Advantages
Experience integrating with LLM APIs (OpenAI, Anthropic Claude, etc.)
Experience with agent frameworks (LangChain, LlamaIndex, AutoGPT)
Background in ML/AI concepts and model deployment
Experience with message queues (RabbitMQ, Kafka) and event-driven architectures
Experience with function calling and tool use patterns in LLMs

Requirements:
5+ years of experience as a Full Stack Engineer in production environments
Strong backend development experience with Python, Node.js, Go, or similar modern backend technologies
Familiar with frontend experience with React, TypeScript, and modern frontend frameworks
Experience designing and consuming REST APIs, event-driven systems, and distributed services
Solid understanding of cloud-native architectures and scalable web applications
Experience working with or integrating AI systems, LLMs, or agent-based architectures.
Strong product mindset and ability to work closely with cross-functional teams
Excellent debugging, problem-solving, and communication skills
Nice to Have
Experience with agent orchestration, context management, or retrieval-augmented architectures
Experience with Kubernetes, Docker, Terraform, or modern DevOps practices
Background in cybersecurity, data-intensive systems, or highly regulated environments.

Requirements:
BSc in Computer Science or a related degree from a recognized institution, or a strong track record in server-side development with advanced technical skills.
4+ years of experience in software engineering with a demonstrated ability to work on large-scale projects and solve complex technical problems.
Proficiency in one or more modern programming languages such as Python, Kotlin, Java, Go, C#, or equivalent, with the ability to adapt to new tools and technologies.
Knowledge about integration of 3rd party tools using RESTful API and the HTTP protocols.
Experience with working with field teams such as Professional Services an Support.
Strong expertise with distributed systems, cloud-native architecture (e.g. Kubernetes, microservices), and APIs.
Hands-on experience with high-throughput date stores and messaging systems (e.g., Snowflake, PostgresSQL, Elasticsearch, Kafka or Redis).
Experience with cloud platforms such as AWS, Azure, or GCP, with knowledge of best practices for deploying and maintaining cloud-based services.
Strong problem-solving skills, with experience debugging and resolving production issues in complex systems.
A proactive approach to task prioritization and a history of leading technical initiatives from conception to deployment with minimal supervision.
Prior experience working in the cybersecurity industry or working with security-centric data pipelines and protocols is advantage.
Bonus: Experience or familiarity with moden frontend frameworks and an understanding of how frontend applications consume and state-manage complex backend data.

Requirements:
8+ years of experience in software development, system design, and architecture roles.
Strong hands-on experience with modern backend technologies such as Java and/or Python.
Practical experience with containerized and cloud-native systems (Docker, Kubernetes, AWS / Azure / GCP).
Experience designing and operating distributed systems, including messaging or streaming platforms (e.g., Kafka, RabbitMQ, Spark).
Solid understanding of distributed databases (and non-distributed) such as Postgres, Cassandra, SingleStore, Clikhouse or similar technologies.
Deep knowledge of engineering best practices: CI/CD, DevOps, testing, security, and agile development.
Proven experience working with production environments, including deployment pipelines, monitoring, and troubleshooting.
Strong problem-solving skills and the ability to balance ideal architecture with real-world constraints.
Natural technical leadership: able to influence, mentor, and collaborate without relying on authority.
Excellent communication skills and the ability to work effectively across teams.
B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent practical experience.

Requirements:
BSc in Computer Science or a related degree from a recognized institution, or a strong track record in server-side development with advanced technical skills.
6+ years of experience in software engineering with a demonstrated ability to work on large-scale projects and solve complex technical problems.
Proficiency in one or more modern programming languages such as Python, Kotlin, Java, Go, C#, or equivalent, with the ability to adapt to new tools and technologies.
Knowledge about integration of 3rd party tools using RESTful API and the HTTP protocols.
Experience with working with field teams such as Professional Services and Support.
Strong expertise with distributed systems, cloud-native architecture (e.g. Kubernetes, microservices), and APIs.
Hands-on experience with high-throughput date stores and messaging systems (e.g., Snowflake, PostgresSQL, Elasticsearch, Kafka or Redis).
Experience with cloud platforms such as AWS, Azure, or GCP, with knowledge of best practices for deploying and maintaining cloud-based services.
Strong problem-solving skills, with experience debugging and resolving production issues in complex systems.
A proactive approach to task prioritization and a history of leading technical initiatives from conception to deployment with minimal supervision.
Prior experience working in the cybersecurity industry or working with security-centric data pipelines and protocols is advantage.
Bonus: Experience or familiarity with modern frontend frameworks and an understanding of how frontend applications consume and state-manage complex backend data.

Requirements:
What You Will Need:
8 or more years of professional experience in software engineering, with significant hands-on experience in AI engineering or applied machine learning.
Strong expertise in building AI-powered systems, including LLM-based applications, agents, and orchestration workflows.
Proven experience integrating and operating AI and ML models in production environments.
Proficiency in multiple programming languages, including Python and at least one of the following: .NET, Go, or similar backend languages.
Experience working across diverse technology stacks and product architectures.
Solid understanding of backend system design, APIs, and distributed systems.
Strong experience with databases, including data modeling, performance considerations, and working with both relational and non-relational systems.
Practical experience with DevOps practices, including CI/CD pipelines, containerization, and cloud-based deployment.
Comfort working in cloud environments and modern infrastructure platforms.
Ability to rapidly prototype, iterate, and evolve ideas into production-ready features.
Strong ownership mindset, curiosity, and ability to collaborate across teams.

Nice to Have:
Experience designing and building AI agents for real-world workflows.
Hands-on experience training, fine-tuning, or evaluating machine learning models.
Familiarity with MLOps practices and model lifecycle management.
Experience working in security, cloud platforms, or large-scale SaaS products.
Ability to communicate complex AI concepts clearly to both technical and non-technical audiences.

Requirements:
What are we looking for?
4+ years of experience as a backend software engineer building production systems.
Proficiency in Python, Node.js, or Go, with a strong focus on clean, maintainable code.
Hands-on experience with AWS serverless services (e.g., Lambda, API Gateway, DynamoDB, SQS/SNS) and infrastructure-as-code.
Experience designing API-driven and event-driven systems.
Strong familiarity with AI development assistants (e.g., Cursor, Claude Code) and active usage in day-to-day development workflows.
Solid problem-solving skills and the ability to work independently in a fast-paced startup environment.

Advantage:
‍‍Experience working on fully serverless systems in production.
Experience with CI/CD pipelines, automated testing, and monitoring in production environments.
Strong communication skills and a collaborative mindset.
Familiarity with frontend technologies (e.g., React, basic frontend architecture) - even if backend is your core focus.

Requirements:
Backend Specialist with a Passion for AI/GenAI, strong systems skills, and eagerness to grow in AI.
5+ years in Python /Java/Scala/C#/ Go
Familiarity with LLM frameworks (LangChain, LangGraph, Haystack, etc.) or willingness to learn.
Basic understanding of prompt engineering, vector databases, and retrieval-augmented generation (RAG).
Solid knowledge of cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Proven track record in building scalable, distributed systems.
Strong problem-solving, ownership, and collaboration skills.
Nice-to-Have Skills:
Exposure to reinforcement learning, multi-agent systems, or autonomous planning.
Interest in ML Ops, AI model deployment, and scaling AI workloads.
Experience with data engineering for AI (ETL pipelines, feature stores, embeddings).
Any experience building AI-powered platforms or agent-based systems.