What are the responsibilities and job description for the Java Backend with AI agent development position at Vidorra Consulting Group?
Location: Moutainview, CA (hybrid 3 days work from office)
Role Overview
We are looking for a hands-on Forward Deployed AI Engineer who can work with business, product, engineering, and client teams to build and deploy AI/GenAI solutions for real business use cases.
This role needs someone who is strong in AI/GenAI development, backend engineering, cloud, problem-solving, and stakeholder communication. The candidate should be able to understand business problems, build AI prototypes, integrate LLMs with enterprise systems, and take solutions from proof-of-concept to production.
The person should be both technical and client-facing, meaning they should be comfortable coding as well as discussing solutions, risks, progress, and outcomes with stakeholders.
Key Responsibilities
Role Overview
We are looking for a hands-on Forward Deployed AI Engineer who can work with business, product, engineering, and client teams to build and deploy AI/GenAI solutions for real business use cases.
This role needs someone who is strong in AI/GenAI development, backend engineering, cloud, problem-solving, and stakeholder communication. The candidate should be able to understand business problems, build AI prototypes, integrate LLMs with enterprise systems, and take solutions from proof-of-concept to production.
The person should be both technical and client-facing, meaning they should be comfortable coding as well as discussing solutions, risks, progress, and outcomes with stakeholders.
Key Responsibilities
- Build and deploy AI/GenAI applications using LLMs, APIs, RAG, agents, embeddings, and enterprise data.
- Create prototypes, proof-of-concepts, and production-ready AI solutions.
- Integrate AI models with backend systems, internal tools, workflows, and applications.
- Work directly with product owners, business teams, engineering teams, and client stakeholders to understand requirements.
- Convert business problems into technical AI solutions.
- Lead demos, solution discussions, status updates, and technical walkthroughs.
- Write clean, maintainable, production-quality code.
- Participate in design reviews, code reviews, debugging, and production issue resolution.
- Ensure AI solutions are secure, scalable, reliable, and properly monitored.
- Work with DevOps/MLOps/platform teams for deployment, CI/CD, monitoring, and release support.
- Partner with AI/ML teams, backend engineers, data teams, QA, product teams, and business users.
- Document solution design, workflows, assumptions, risks, and support handoff details.
- Hands-on experience building AI/GenAI applications.
- Experience with LLMs, prompt engineering, RAG, agents, embeddings, or vector databases.
- Strong programming experience in Python and/or Java.
- Backend development experience with APIs, microservices, integrations, and enterprise systems.
- Cloud experience, preferably AWS.
- Ability to understand business problems and design technical AI solutions.
- Strong communication and stakeholder management skills.
- Comfortable working in fast-paced and ambiguous environments.
- Strong ownership, problem-solving, and hands-on delivery mindset.
- Experience with AWS Bedrock, SageMaker, Lambda, ECS/EKS, API Gateway, EC2, MSK/Kafka.
- Experience with LangChain, LlamaIndex, OpenAI APIs, Claude, Gemini, Hugging Face, or similar AI tools.
- Experience with vector databases such as Pinecone, FAISS, Weaviate, Chroma, Milvus, or OpenSearch.
- Experience with MLOps, model evaluation, monitoring, guardrails, and responsible AI.
- Domain experience in fintech, tax, accounting, payments, small business, CRM, sales, or financial platforms.
- Prior experience as a Forward Deployed Engineer, AI Engineer, Applied AI Engineer, AI Solutions Engineer, or AI Product Engineer.
- 5 years of software engineering experience, with recent hands-on AI/GenAI project experience.
- Experience taking applications from concept to production.
- Experience working with distributed teams and cross-functional stakeholders.
- Exposure to CI/CD, automated testing, observability, monitoring, and cloud-native development.
- Ability to work with senior stakeholders, product teams, managers, directors, and engineering leadership.