Azure AI Architecture
LTM
About the role
Role & responsibilities We are seeking a highly skilled Forward Deployed AI Engineer to work directly with customers understand business challenges and design develop and deploy AI solutions with deep expertise in opensource AI technologies The ideal candidate combines strong software engineering expertise with hands-on experience in implementing Agentic AI solutions using cutting edge opensource frameworks vector databases and LLM orchestration platforms Preferred candidate profile Responsible for planning designing and building AI applications leveraging LLMs and Agentic AI frameworks Understand customer requirements and own projects from concept through production deployment Design and implement single agent and multiagent AI solutions with guardrails using opensource AI frameworks Develop scalable RAG architectures using vector databases and embedding models Package test optimize and deploy AI agents in cloud and on premises environments Implement monitoring evaluation and observability mechanisms for AI systems Write high performing standards compliant code and conduct code reviews Perform technical feasibility assessments and recommend solution architectures Work directly with customers to solve complex AI transformation challenges Stay current with emerging open-source AI technologies and contribute best practices to engineering teams
Mandatory Skills
- 12 years of software engineering experience with minimum of 3 years experience in building AI solutions AI agents A2A MCP and agent communication standards Handson experience in implementing Agentic AI features AI agent orchestration patterns RAG solutions Customer facing consulting experience Excellent communication and stakeholder management skills Ability to translate business requirements into AI powered solutions Experience in prompt engineering and evaluation frameworks Experience in implementing AI safety monitoring responsible AI and guardrails Handson experience using AI Framework like LangChain LangGraph CrewAI etc Proficiency in Python Tools/Technologies: Development Advanced Python REST APIs Async Programming Microservices Architecture Software
- Design Patterns Distributed Systems LLM Frameworks LangChain LangGraph CrewAI LlamaIndex Haystack LLM Models Azure OpenAI Service GPT4o GPT4x oseries models DeepSeek Mistral Llama Monitoring Evaluation LangSmith Deep Eval OpenTelemetry Prompt Evaluation AI Observability Performance Optimization Machine Learning Embeddings Hugging Face Transformers Hugging Face Inference APIs Sentence Transformers Embedding Models Agentic AI SingleAgent Systems MultiAgent Systems Autonomous Agent Frameworks Agent Memory Tool Calling Workflow Orchestration HumanintheLoop
- Design Infrastructure Azure Docker Azure Kubernetes Vector Databases Pinecone FAISS ChromaDB
Eligibility & process
Who can apply
Experience: 12-16 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
19 resourcesStudy material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Explain the difference between Precision, Recall, and F1-Score. Answer
How does Gradient Descent work and what is the role of Learning Rate? Answer
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Behavioural & HR questions 3
Highlight LTM's market reputation, recent tech innovations, and how your skills in Microsoft Azure directly solve their team's objectives.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package (Best in Industry)
India (Remote / Multiple), India
Experience: 12-16 Yrs. Open to matching qβ¦
