{"id":24724,"url":"https://alion.io/job/reindeercompany-software-engineer-backend","title":"Software Engineer (Backend)","company":{"id":6743,"name":"Reindeer","domain":"reindeercompany.com","url":"https://alion.io/company/reindeercompany","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tel Aviv, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":92000,"max_usd":270000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":6933},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon DocumentDB","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"HIPAA","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"CI/CD","optional":true},{"name":"Go","optional":true},{"name":"Neo4j","optional":true},{"name":"Rust","optional":true}],"status":"live","first_seen_at":"2025-07-17T11:43:59Z","employer_posted_date":"2025-07-17","last_verified_at":"2026-10-18T02:58:55Z","board_verified":true,"closed_at":null,"days_open":457,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":457},"description":"We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact.\nWe believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in.\nWe are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.\nYour Impact\nAI Agent Development\nDesign and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management.\n\nImplement reinforcement learning techniques to enhance decision-making capabilities of AI agents.\n\nAI Integration\nBuild and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM).\n\nUse frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing.\n\nData Processing and Pipelines\nDesign and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently.\n\nOptimize data handling to improve speed and accuracy of AI agents.\n\nSecurity and Compliance\nImplement authentication and authorization mechanisms to secure AI-driven systems.\n\nEnsure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling.\n\nCloud Infrastructure and Scalability\nDeploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.\n\nLeverage containerization (Docker, Kubernetes) for efficient deployment and management.\n\nTesting and Optimization\nDevelop and execute unit, integration, and performance tests for AI-driven systems.\n\nContinuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.\n\nCollaboration\nWork closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements.\n\nParticipate in code reviews, design discussions, and architecture planning to drive innovation.\n\nWhat It Takes\nExperience\n5+ years of experience in software engineering with a focus on AI-driven or autonomous systems.\n\nProven track record of deploying AI models or agents in production environments.\n\nTechnical Skills\nProficiency in Python.\n\nDatabases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (e.g. Document DB, Vector DB).\n\nCloud: Experience deploying large scale production applications on AWS, GCP, or Azure.\n\nSecurity: Understanding of OAuth2, JWT, and best practices for securing systems.\n\nNice To Have\nAI Frameworks: Experience with TensorFlow, PyTorch, or Hugging Face.\n\nExperience with RPA (Robotic Process Automation) tools\n\nFamiliarity with graph databases (Neo4j) for managing complex workflows.\n\nFamiliarity with Go and Rust\n\nExperience with CI/CD pipelines and DevOps 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