{"schemaVersion":"jobsearcher.job.v1","id":"4ff6d792e441e4b9606eb9ee","url":"https://jobsearcher.com/jobs/4ff6d792e441e4b9606eb9ee","canonicalUrl":"https://jobsearcher.com/jobs/4ff6d792e441e4b9606eb9ee","title":"Full Stack Developer-AI","description":"Full Stack Developer-AILocation: Jersey City, NJ (5 Days Onsite) Duration: 6+ Months Only W2Required Qualifications, Capabilities, and SkillsMS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).Minimum 7 years of development experience, with at least 4 years working on AI/ML solutions.Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.Hands-on experience owning retrieval or recommendation quality in a production system, with the metrics and evaluation discipline to prove improvement.Practical RAG experience — retrieval quality, embeddings, and vector stores; Graph RAG a strong plus.Strong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.Knowledge of Kubernetes (AWS EKS).Experience with training models in Databricks and SageMaker.Experience working with MLflow.Expert knowledge of at least one of: AWS, Azure, Kubernetes.Knowledge of data management and data model design; real-time processing using both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis).Excellent communication skills with the ability to partner effectively with senior technical and business stakeholders.Preferred Qualifications, Capabilities, and SkillsExperience with recommendation, propensity, ranking, or learning-to-rank models in a production setting.Experience with NLP and information retrieval at scale: document understanding and extraction, summarization evaluation, reranking, or speech-to-text and call intelligence.Experience with online experimentation and interleaving for retrieval or recommendation quality.Experience with CRM data (Salesforce objects, Data Cloud) and with modelling over sales pipeline and engagement data.Experience delivering models through model risk management or equivalent regulatory review, including supervision of client-facing generated content.Experience working in the financial or payments domain at a large institution (Investment Banking, Markets, Securities Services, or adjacent), or with sales enablement and client service platforms.Experience with agent frameworks or runtimes, A2A, or MCP.Agent memory design (memory nodes, episodic/semantic memory) and organizational context management.Knowledge graphs and graph databases used for retrieval.Understanding of LLM fine-tuning and small language model inference.Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK).Knowledge of high-performance languages such as Go or Rust.","company":"Apolis","rawCompany":"apolis","city":"Jersey City","state":"NJ","isRemote":false,"isActive":false,"createdAt":"2026-10-19T13:37:54.133Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1254.00","title":"Web Developers","slug":"web-developers"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Full Stack Developer-AI","description":"Full Stack Developer-AILocation: Jersey City, NJ (5 Days Onsite) Duration: 6+ Months Only W2Required Qualifications, Capabilities, and SkillsMS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).Minimum 7 years of development experience, with at least 4 years working on AI/ML solutions.Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.Hands-on experience owning retrieval or recommendation quality in a production system, with the metrics and evaluation discipline to prove improvement.Practical RAG experience — retrieval quality, embeddings, and vector stores; 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