Artificial Intelligence Senior Associate

V2

Soft Job Opportunity

V2

Soft is a global leader in IT services and business solutions, delivering innovative and cost-effective technology solutions worldwide since 1998. We partner with Fortune 500 companies to address complex business challenges. Our services span AI, IT staffing, cloud computing, engineering, mobility, testing, and more. Certified with CMMI Level 3 and ISO standards, V2

Soft is committed to quality and security. Beyond our work, we actively support local communities and non-profits, reflecting our core values. Join us to be part of a dynamic and impactful global company!

Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming.

Key Responsibilities:

• Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities
• Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence
• Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming
• Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation

Google Cloud Platform

Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1–2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production — not just notebooks or demos. Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks — Lang Graph, CrewAI, Llama Index, or equivalent — for building stateful, multi-step, tool-using agent workflows.

Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (Big Query, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, Git Hub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems — offline eval sets, LLM-as-judge scoring, and tracing tools (Lang Smith, Langfuse, Open Telemetry, or equivalent) to track task success, latency, and cost.

Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices.

1. Experience with cost optimization and model routing — designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale.
2. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases.
3. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data.
4. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents.
5. Prior experience in a startup or 0-to-1 product environment,…