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CLOUD SPECIALIST – CUSTOMER ENGINEERING @ LOVAS IT

0 Negotiable or Not Mentioned India 6 days ago lovasit.com 377 Views

Lovas IT is looking for a dynamic Cloud Specialist – Customer Engineering who can bridge the gap between complex engineering depth and customer-facing consulting. This role is specifically designed for a professional who can build solutions and pitch them with equal confidence, acting as a technical liaison to help customers design, evaluate, and adopt cloud-based solutions. The candidate will be responsible for translating technical architecture into clear business value, ensuring real-world application architecture is optimized for the cloud platform. The possible work locations for this role include Mumbai, Delhi, Bangalore, Mangaluru, Udupi, and Chennai.

The ideal candidate is expected to have a software engineering background with a transition into cloud specialism, specifically with experience in Google Cloud Platform (GCP) or cloud-native applications. You will be tasked with preparing solution scopes, effort estimations, and technical documentation, as well as delivering whiteboarding sessions and live demos. This position requires a mindset that is 60% engineer and 40% consultant, making it a perfect fit for individuals from product companies or GCP-native startups who enjoy high levels of customer interaction and solution storytelling.

Key Requirements

4 to 6 years of relevant professional experience. Strong communication and presentation skills are critical. Proven experience in Solution Architecting and Technical Leadership. A solid background in Full Stack development. Exposure to Presales, Customer Engineering, or Solution Sales roles. Ability to confidently interact with both business and technical stakeholders. Hands-on experience with GCP (Google Cloud Platform) or cloud-native applications. Comfortable performing live demos and whiteboarding sessions. Ability to build prototypes and integrations in various customer environments. Expertise in preparing solution scopes and detailed technical documentation.
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CLOUD LEADER – AGENTIC AI (ARCHITECT LEVEL ROLE) @ LOVAS IT

0 Negotiable or Not Mentioned India 6 days ago lovasit.com 377 Views

Lovas IT is seeking a highly skilled Cloud Leader – Agentic AI to architect and lead next-generation enterprise AI platforms built on multi-agent systems. This is an architect-level role requiring significant experience in building and deploying agent-based systems in production environments. The successful candidate will own the end-to-end architecture of Agentic AI systems powering enterprise use cases such as policy lifecycle, underwriting, and claims. This position is available across multiple locations in India, specifically Mumbai, Bangalore, Mangaluru, and Udupi.

The role involves defining agent orchestration, memory management, tool usage, and guardrails while optimizing systems for latency, cost, and reliability. You will collaborate with product, engineering, and domain teams to establish evaluation frameworks and AI safety controls. Ideal candidates should have deep expertise in the Google ADK and the GCP ecosystem, specifically Vertex AI. You must be capable of handling real-world challenges beyond theoretical models, ensuring safe, scalable, and cost-efficient AI deployments.

Key Requirements

Minimum of 7.5 to 12 years of experience in architecture focusing on AI/ML and distributed systems. Hands-on experience with Large Language Models (LLMs) including Prompting, RAG, Fine-tuning, and Evaluation. Proven experience in agent-based or LLM-driven system design within a production environment. Strong knowledge of microservices and event-driven architectures. Demonstrated expertise in Agentic AI Architecture as a core technical skill. Ability to architect multi-agent systems using the Google Agent Development Kit (ADK). Experience defining agent orchestration, memory management, tool usage, and AI guardrails. Skills in designing LLM + API + workflow + event-driven architectures. Capability to optimize systems for latency, cost, reliability, and observability. Experience establishing evaluation frameworks, prompt strategies, and AI safety controls.
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