Visionary AI Innovator

6 days ago

vijayawada, India beBeeArtificialIntelligence Full time

Join Our Vision for AI InnovationA Role in AI Engineering with End-to-End ResponsibilityOverviewWe are on a mission to revolutionize user experiences through production-grade AI workflows and agentic applications. As an AI Engineer, you will be working closely with our product and engineering teams to ship features that make a real impact.Our ideal candidate has hands-on experience with Large Language Models (LLMs), orchestration frameworks, and Python development. You should have a strong understanding of agent patterns, workflow engines, and prompt design principles.We value collaboration, a strong debugging mindset, and a bias towards shipping high-quality work. If you're passionate about building innovative solutions that power real user experiences, we want to hear from youResponsibilitiesDesign, build, and iterate LLM-powered workflows, including retrieval, routing, tool use, function calling, and multi-step agents.Implement agentic apps that plan, call tools/APIs, and maintain state across tasks.Develop RAG pipelines for data ingestion, chunking, embeddings, indexing, and latency-optimized retrieval.Own prompt engineering & evaluation, including A/B tests, guardrails, metrics like latency, cost, quality, and safety.Productionize models/workflows with observability, cost controls, and fallbacks.Ship backend services and APIs integrating with data stores and vector DBs.Collaborate with PM/Design to translate requirements into reliable, user-facing features.RequirementsHands-on experience with LLMs (OpenAI, Claude, Llama, etc.) and orchestration frameworks (LangChain, LlamaIndex, or custom).Python proficiency, including building RESTful services and writing clean, tested code.Experience with RAG, vector databases (Pinecone, Weaviate, FAISS, Qdrant), embeddings, and related technologies.Understanding of agent patterns, workflow engines, and prompt design principles.Familiarity with cloud deployment (AWS/GCP/Azure), Docker, Git, CI/CD, and related concepts.Strong debugging mindset and bias towards shipping high-quality work.Nice-to-Have SkillsFastAPI/Flask, Celery/queues; streaming UIs.Model fine-tuning/LoRA, dataset curation, prompt-cache strategies.Monitoring/tracing (LangSmith, Weights & Biases, OpenTelemetry).Frontend basics (React/Next.js) to collaborate on UX.Data privacy, PII redaction, and security best practices.Success MetricsReduction in latency/cost per request.Improvement in answer quality scores.Workflow reliability (timeouts, retries, fallbacks) and on-call readiness.Speed of iteration from spec → prototype → production.

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