{"id":3425226,"url":"https://alion.io/job/inallmedia-backend-engineer-ai-agentic-19041905","title":"Backend Engineer (AI Agentic) 1904/1905","company":{"id":4431647,"name":"InAllMedia","domain":"inallmedia.com","url":"https://alion.io/company/inallmedia","size_band":"11-50","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":{"grade":"A","score":95,"open_postings":33,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":236,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":{"label":"CT","utc_offset_min":-6,"utc_offset_max":-6},"hiring_geo_confidence":"structured","locations":["Brazil"],"countries":["BR"],"hiring_countries":["AR","BR","CO","MX","AI","AG","AW","BS","BB","BZ","BM","BO","VG","BQ","KY","CL","CR","CW","DM","DO","EC","SV","FK","GF","GD","GP","GT","GY","HT","HN","JM","MQ","MS","NI","PA","PY","PE","PR","KN","LC"],"hiring_countries_total":49,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":108000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":19},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Weaviate","optional":false},{"name":"Docker","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangSmith","optional":true},{"name":"Pandas","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-15T16:02:12Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-11-13T07:46:25Z","board_verified":true,"closed_at":null,"days_open":58,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":58},"description":"Position: Backend Engineer (AI Agentic)\nLocation: Remote from LATAM\nContract Type: Full-time Contractor\nTime Zone Alignment: CT\nAbout In All Media\nWe are a Managed Nearshore Teams provider headquartered in Austin, specializing in building and embedding high-performing software development teams. From design to deployment, we deliver customized solutions by connecting global talent with innovative client projects. Our model allows you to work on international challenges, collaborate with diverse teams, and grow your career while being part of a company that values expertise, creativity, and impact.\nProject Overview\nIn this role, you will be at the forefront of the AI revolution, supporting a high-impact project focused on autonomous agents and intelligent backend architectures. You will join a collaborative, fast-paced team dedicated to building the next generation of AI-driven solutions. The project involves architecting sophisticated agentic workflows and leveraging advanced retrieval techniques to power business intelligence at scale. As a Backend Engineer (AI Agentic), you will be instrumental in transforming raw data and LLM capabilities into reliable, goal-oriented AI systems.\nKey Responsibilities\nAgentic Development: Design and implement complex AI agents and multi-agent workflows using frameworks like LangChain or LangGraph.\nBackend Architecture: Build and maintain scalable, high-performance backend services using Python to support AI-driven features.\n RAG Implementation: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines to provide agents with accurate, context-aware information.\n Vector Database Management: Architect and manage vector storage solutions (Pinecone, Weaviate) to ensure efficient similarity search and data retrieval.\n System Integration: Integrate Large Language Models (LLMs) with existing APIs and third-party services to enhance agent capabilities.\nAgile Collaboration: Work closely with product owners, data scientists, and fellow engineers to translate ambitious AI requirements into production-ready code.\nMust-Have Skills\nAI Frameworks: Deep expertise in LangChain, LangGraph, or Semantic Kernel. ( 3 + YEARS OF EXPERIENCE)\nBackend Mastery: Senior-level proficiency in Python ( 6 + YEARS OF EXPERIENCE) and its ecosystem for building robust APIs.\nVector Databases: Proven experience working with Pinecone, Weaviate, or similar vector search engines.\nAI Specialization: Strong understanding of Retrieval-Augmented Generation (RAG) and agentic design patterns.\nSoft Skills: A truly collaborative team player mindset with an appetite for solving ambiguous, cutting-edge problems.\nFluent English: Excellent verbal and written communication skills for daily technical collaboration and documentation.\nNice-to-Have Skills\nCloud & Orchestration: Experience deploying AI workloads on Kubernetes or Docker.\nPrompt Engineering: Knowledge of advanced prompting techniques and LLM fine-tuning.\nData Engineering: Familiarity with data processing libraries like Pandas or Spark.\n Monitoring: Experience with tools for monitoring LLM performance and cost (e.g., LangSmith).\nTime Zone & Collaboration\nThis role is 100% remote from LATAM and requires consistent overlap with teams in Central Time (CT). 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