דרושים » הנדסה » Senior Software Engineer - AI Security

Requirements:
5+ years of software engineering experience, with at least 2 years in Python.
Experience building back-end services using microservices architecture.
Proficiency with both SQL and NoSQL databases.
Strong background in designing scalable, distributed systems.
Hands-on experience in CI/CD environments and modern testing frameworks.
Solid understanding of TDD and a quality-first engineering mindset.
Excellent communication skills in English.
🌟 Bonus Points For:
B.Sc. in Computer Science, Engineering, or equivalent experience.
Startup experience or work in multidisciplinary tech environments.
Experience with multi-threaded or multi-tasked applications.
Hands-on with AWS (e.g., Lambda, SQS, CloudFront, EKS).
Familiarity with Docker, Kubernetes, and RESTful services.
Exposure to computer vision or AI-driven systems.
Background in video systems (streaming, encoding, media servers).
Experience with any of our stack: GitLab, InfluxDB, RabbitMQ, MongoDB, PyTorch.

Requirements:
6+ years of experience in DevOps, MLOps, or infrastructure roles with a focus on ML model delivery.

Proven hands-on experience deploying GPU-based models (LLMs, vision, transformers) using vLLM or Triton.

Deep knowledge of AWS EKS and Kubernetes, with practical experience configuring Karpenter and KEDA for auto-scaling GPU workloads.

Experience building pipelines using Jenkins, GitHub Actions, and managing releases for ML and application codebases.

Familiarity with AWS SageMaker, ClearML, or similar platforms for ML orchestration and experimentation.

Strong scripting and automation skills in Python, Bash, and working knowledge of containerization (Docker).

Solid grasp of networking, IAM, and cloud security fundamentals.

Requirements:
Requirements:
5+ years of experience as a backend/software engineer, preferably in Python, Go, or Java.
Strong experience with designing APIs, building microservices, and integrating third-party services.
Familiarity with ML workflows: model serving, feature extraction, and batch vs real-time inference.
strong architectural/design skills, including working with message queues like Kafka, relational and NoSQL databases, and distributed systems.
Experience deploying services in containerized environments (e.g., Docker, Kubernetes).
Proficient with cloud-native tools or on-prem equivalents (e.g., logging, tracing, metrics).
Knowledge of data processing frameworks (e.g., Pandas, Spark, Airflow) is a plus.
Comfortable reading and working with Python-based ML code (scikit-learn, TensorFlow, PyTorch, etc.).
Strong ownership mindset and a collaborative attitude.

Nice to Have:
Experience with model versioning and ML serving frameworks (e.g., MLflow, Seldon, Triton).
Understanding of data privacy/security implications in model and data pipelines.
Experience working in cross-functional teams with data scientists and product owners.

Requirements:
BA or B.Sc in Computer Science or an equivalent field
5+ years of hands-on experience in SW development.
Strong proficiency in at least one backend programming language (Java, Python).
Strong understanding of object-oriented programming, design patterns, and clean code principles
Familiarity with database systems (SQL/NoSQL) and query optimization techniques
Proven experience of cloud platforms (AWS, Azure, GCP) and microservices architecture
Strong understanding of REST API
Excellent problem-solving skills and a proactive attitude
Strong communication skills and the ability to collaborate in a team environment
Advantages:
Experience with Spring Boot and the Spring Framework ecosystem
Experienced with JPA (Hibernate advantage)
Experience with streaming or messaging services (Kafka, RabbitMQ)
Knowledge of monitoring tools such as Grafana, Prometheus, or ELK Stack
Hands-on experience with containerization and orchestration (Docker, Kubernetes)
Familiarity with big data technologies like Apache Flink or Spark
Experience in performance optimization and distributed systems.

Requirements:
BSc in Computer Science or a related field.
6+ years of experience building and deploying ML systems in production environments.
Proficiency in Python and production frameworks like FastAPI, Databricks, SageMaker, and MLflow.
Proven track record in deploying and maintaining ML/LLM services (APIs, microservices, serverless, or containerized).
Strong understanding of software engineering fundamentals: object-oriented design, testing, version control, CI/CD, and performance optimization.
Experience working with agentic workflows or LLM-based agents.
Ability to work independently and break down complex, ambiguous problems into structured solutions.
Strong communication skillsable to explain technical concepts to both technical and non-technical stakeholders.
Advantages:
Hands-on experience with Kubernetes, Airflow, Spark, ArgoCD, and Docker.
Experience working with databases such as Elasticsearch, vector databases, PostgreSQL, and SQL.
Experience fine-tuning or integrating open-source LLMs in production environments (e.g., RAG, LoRA, agent frameworks).
Contributions to open-source ML or MLOps projects.

Requirements:
5+ years of experience as a backend engineer building large-scale products.‍
Proficiency in Python/Node/Go with a passion for writing clean, maintainable code.‍
Hands-on expertise with AWS services (e.g., Lambda, API Gateway, DynamoDB, ECS) and infrastructure-as-code.‍
Proven track record designing microservice architectures; deep serverless and event-driven architecture experience is a big plus.‍
Advantage:
‍‍Experience deploying and operating applications on Kubernetes (K8s) clusters.
Strong problem-solving skills, excellent communication, and a desire to thrive in a fast-paced startup environment.
Solid grasp of CI/CD pipelines, automated testing, and monitoring in production.
Service in elite tech units (e.g., 81, 8200, Talpiot) or equivalent experience is a nice-to-have.

Requirements:
5+ years of professional experience as a backend developer, with strong skills in Python
Solid experience in developing services on cloud platforms, particularly AWS (experience with Azure or GCP is a plus).
Expertise in Python frameworks and Node.js frameworks (e.g., Express).
Strong understanding of software engineering principles, including system design and data structures.
Experience building RESTful APIs and microservices architectures.
Familiarity with relational and NoSQL databases (e.g., MySQL, MongoDB).
Strong debugging, performance optimization, and troubleshooting skills.
Strong communication and collaboration skills, with the ability to work effectively in a team.
Proactive, detail-oriented, and self-motivated with the ability to thrive in a fast-paced environment.
Nice-to-Have:
Experience with Node.js
Knowledge of serverless architecture (e.g., AWS Lambda).
Experience with DevOps tools and practices, including:
Infrastructure as Code (IaC) tools like Terraform.
Containerization and orchestration tools like Docker and Kubernetes (K8s).
CI/CD tools such as Jenkins or similar.
Knowledge of security best practices for cloud-based environments.
Previous experience working in an infrastructure or architecture team.

Requirements:
5+ years of experience as an engineer
Proven experience working and creating AI-based tools and workflows
Passionate about AI, tools for developers and developer experience
Good communication skills
Delivery oriented and ready to make things happen

Requirements:
Must:
BSc in Computer Science or related degree, or equivalent practical experience.
4+ years of hands-on experience as a software Engineer
Strong proficiency in Python and experience with AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Experience with AI APIs (OpenAI, Anthropic, Google AI, Microsoft AI) and integrating them into engineering workflows
Hands-on experience with developer productivity tools, AI-enhanced automation, and knowledge management systems
Strong problem-solving skills and ability to build AI-powered solutions that engineers love to use.
Nice to Have:
Deep understanding of LLMs, RAG (Retrieval-Augmented Generation), fine-tuning, and prompt engineering.
Experience with data pipelines, embeddings, and vector databases for AI-powered search and automation.
Experience working with cloud-based AI platforms and scalable AI architectures
Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for deploying AI applications.
Experience with AI Ops, observability tools, and monitoring AI applications in production.
Familiarity with LangChain, AutoML, MLOps frameworks, and workflow automation tools.
A background in software engineering, DevOps, or developer tooling.
Strong entrepreneurial mindset, able to identify opportunities, move fast, and drive AI adoption in a high-impact environment.
Published research, open-source contributions, or side projects demonstrating innovative AI applications.
Why Join Us?
This role is for builders, problem-solvers, and AI enthusiasts who want to push the boundaries of engineering productivity with AI. Youll be at the forefront of AI-powered platform engineering, shaping how our company leverages AI to supercharge innovation, efficiency, and automation.
If youre looking to build game-changing AI platforms, experiment with cutting-edge tech, and make a real impactjoin us!