{"id":3237087,"url":"https://alion.io/job/arrowhead-software-engineer","title":"Software Engineer","company":{"id":5099,"name":"Arrowhead","domain":"arrowhead.team","url":"https://alion.io/company/arrowhead","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":9000,"max_usd":23000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":43},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Kubernetes","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"WebSockets","optional":false},{"name":"NLP","optional":true}],"status":"live","first_seen_at":"2026-10-25T12:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-25T12:35:00Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"You will be responsible for building and optimizing a highly scalable real-time voice AI platform that supports speech processing, conversational AI, and automated call handling. The system is built using FastAPI and WebSockets, running in a Kubernetes-based environment with event-driven architecture.\n\nResponsibilities: \nDesigning and optimizing a real-time voice processing pipeline that integrates speech-to-text, intelligent response generation, and text-to-speech synthesis.\nManaging a scalable call orchestration system, efficiently scheduling and executing high-volume automated interactions.\nImplementing asynchronous, event-driven workflows to ensure high throughput and low-latency responses.\nScaling infrastructure using Kubernetes with auto-scaling mechanisms for high availability.\nEnhancing system observability through logging, health checks, and performance monitoring.\n\nRequirements: \n4+ years of backend engineering experience (Python preferred).\nExpertise in FastAPI, WebSockets, and event-driven architectures.\nStrong understanding of asynchronous programming and concurrency in Python.\nExperience with Kubernetes, Docker, and cloud-based deployments.\nKnowledge of speech processing, text-to-speech generation, and conversational AI systems.\nExperience with databases (PostgreSQL, Redis) and scalable data handling.\nStrong debugging and performance optimization skills for high-throughput systems.\n\nGood to Have: \nExperience in telephony integrations for call handling and scheduling.\nBackground in natural language processing (NLP) and AI-driven assistants\nExperience with monitoring tools and logging frameworks for system observability.\nFamiliarity with distributed systems, load balancing, and autoscaling techniques.\nSkills\nfastapi, python, websocket, 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