{"id":2461540,"url":"https://alion.io/job/wit-software-senior-generative-ai-engineer","title":"Senior Generative AI Engineer","company":{"id":54049,"name":"WIT Software","domain":"wit-software.com","url":"https://alion.io/company/wit-software","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":111000,"max_usd":245000,"period":"year","method":"global_role_seniority_cell","sample_n":1986},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Tool Use","optional":false},{"name":"Agile","optional":true},{"name":"AI Agents","optional":true},{"name":"Anthropic","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Claude","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Gemini","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Llama","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Machine Learning","optional":true},{"name":"Milvus","optional":true},{"name":"Mistral","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"OpenAI","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-10-13T15:24:21Z","employer_posted_date":null,"last_verified_at":"2026-10-13T15:24:21Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"This is a remote position.WIT Software creates products and solutions for the Telecom industry and has a strong background in Messaging, IP Voice and Video, Unified Communications, Telecom Services, TV Middleware and Mobile Money. With 25 years of experience, WIT works with some of the world's leading Telecom operators across Europe, Japan, the United States and Africa. \nWIT is developing an innovative AI-powered platform that leverages the latest advances in Generative AI to enable the creation of next-generation digital services for the Telecom industry. This product has the potential to be adopted by hundreds of mobile operators and service providers, reaching millions of users across multiple geographies worldwide.\nWe are looking for an experienced Generative AI Engineer to join our Product Team. This is an exciting opportunity for someone passionate about designing scalable software solutions, building production-ready AI applications and applying Generative AI technologies to solve complex real-world challenges.\nResponsibilities\n\nDesign, develop and maintain scalable backend services for AI-powered applications.\n\nDesign and implement production-ready Generative AI solutions using Large Language Models (LLMs).\n\nDesign, optimize and evaluate Retrieval-Augmented Generation (RAG) or tool-based pipelines and AI orchestration workflows, including chunking strategy, hybrid retrieval and reranking, and retrieval-quality evaluation.\n\nDesign scalable APIs, distributed systems and vector search solutions.\n\nEvaluate, integrate and optimize foundation models for different use cases.\n\nOptimize AI systems for performance, scalability and reliability.\n\nCollaborate with cross-functional teams to define technical solutions and product evolution.\n\nContribute to software architecture, technical documentation and engineering best practices.\n\nResearch and evaluate emerging AI technologies.\n\nLead design reviews, define engineering standards and mentor engineers on Generative AI best practices.\n\nRequirements\n\nDegree in Computer Science, Software Engineering or a related field. \n\n5+ years of professional experience in software development.\n\n2+ years of hands-on experience designing and building Generative AI applications using Large Language Models (LLMs).\n\nHands-on experience with speech and multimodal models, including speech-to-text (STT), text-to-speech (TTS), speech-to-speech and vision-capable LLMs that process images.\n\nProficiency using and building applications on top of these models, including real-time (streaming) and Completions/Responses APIs, tool calling, model deployment and model evaluation.\n\nStrong experience with scalable backend systems and distributed architectures.\n\nStrong proficiency in Python, including asynchronous and concurrent programming for I/O-bound LLM workloads.\n\nSolid understanding of software engineering best practices, including design patterns, testing and CI/CD.\n\nExperience with RESTful APIs, microservices and event-driven architectures.\n\nExperience building production-ready AI applications.\n\nExperience defining and applying structured evaluation methodologies for LLM and RAG systems (for example, retrieval and generation quality metrics).\n\nKnowledge of cloud-native architectures, containerization and orchestration technologies.\n\nUnderstanding of responsible AI and security practices, including data privacy, prompt-injection defense and safe handling of model outputs.\n\nStrong analytical, problem-solving and communication skills.\n\nAbove all, strong product intuition and a sharp sense for user experience, with the ability to build AI solutions that feel intuitive and reliable for end users.\n\n· Fluent in English.\nPreferred Skills\n\nHands-on experience designing Retrieval-Augmented Generation (RAG) solutions.\n\nProficiency with LangChain, LangGraph or LlamaIndex.\n\nExperience integrating foundation models such as OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama or Mistral.\n\nKnowledge of vector databases, including Pinecone, Milvus, Weaviate or pgvector.\n\nExperience designing AI Agents and multi-agent systems.\n\nUnderstanding of prompt engineering, model evaluation and AI observability.\n\nProficiency with Machine Learning frameworks such as PyTorch or TensorFlow.\n\nKnowledge of cloud platforms (AWS, Azure or Google Cloud).\n\nFamiliarity with Kubernetes, Docker and modern DevOps practices.\n\nExperience working in Agile software development environments.\n\nBenefits\nWe offer a competitive compensation package as well as an environment conducive to personal and professional growth.\n\nOriginally posted on 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