Head AI Systems & Operations

Shivalik Design Pvt Ltd — GOTS-certified garment export house in Faridabad, Haryana, manufacturing for UK/EU brands. We are hiring for a full-time, on-site role in Faridabad.

About the role:

We are building AI-driven automation across our factory and export operations. As AI Automation Lead (Operations), you will design, build, and own AI/automation workflows that connect our ERP, WhatsApp, Google Sheets, and email — and roll them out across production, quality, merchandising, and logistics.

Responsibilities:

- Design and deploy automation workflows across ERP, WhatsApp Business, Google Sheets/Drive, and email.

- Build and maintain LLM-powered agents for document processing, query handling, status updates, and reporting.

- Own the automation backlog for factory operations: production planning, dispatch tracking, sample approvals, QC, inventory, and shipping documentation.

- Integrate internal systems (ERP, PLM, messaging) via APIs, webhooks, and low-code platforms.

- Set standards, document flows, train operations staff, and measure impact (time saved, error rate, throughput).

- Collaborate with IT and operations leadership on data, security, and scaling.

Requirements:

- 3–5 years experience with n8n, Make (Integromat), Python, and LLM agents.

- Hands-on automation across ERPs, WhatsApp Business API, Google Workspace (Sheets, Drive, Gmail, Calendar), and email workflows.

- Strong Python; comfort building REST API connectors, webhooks, and scheduled jobs.

- Experience prompting, fine-tuning, or orchestrating LLMs (OpenAI, Anthropic, Gemini, open-source) into agentic workflows.

- Comfort working on-site with factory/operations teams and translating business needs into automation.

Nice to have:

- Garment/apparels/exports domain experience.

- Experience with SAP, Oracle, Tally, Zoho, or similar ERPs.

- Knowledge of OCR, document extraction, and structured data pipelines.

Compensation: ₹14–24 LPA, full-time, on-site at Faridabad (Haryana).

Job Title: Chief of Staff (AI & Data-Driven Strategy) 

Company: StarApps Studio 

Experience: 4+ years 

Location:Pune (On-site) 

About StarApps Studio 

StarApps Studio is a fast-growing Shopify app development company building high-impact ecommerce SaaS products for global merchants. We operate in a high-ownership, fast-execution environment where data, clarity, and speed matter.

Role Overview 

We are looking for a highly analytical and operational Chief of Staff to serve as the right-hand strategic partner to our founders and leadership team. This role is a force multiplier—you will drive executive execution, improve high-level decision-making, and lead strategic initiatives across the company. This requires strong analytical thinking, AI fluency, and the operational rigor to turn visionary ideas into measurable results.

Key Responsibilities

• Executive Strategy & Alignment: Act as a strategic partner to founders by managing business priorities and driving key organizational deliverables.
• Cross-Functional Leadership: Own the execution of high-impact cross-functional initiatives across Product, Growth, Support, and Operations.
• Business Intelligence: Build dashboards, trackers, and comprehensive reports to empower data-backed leadership decision-making.
• AI & Operational Excellence: Leverage AI tools (ChatGPT, automation, analytics) to aggressively optimize workflows and scale internal productivity.
• Operating Rhythm: Drive the cadence of leadership by preparing strategic meeting agendas, synthesizing notes, and ensuring relentless closure on action items.
• Market & Product Strategy: Conduct deep-dive market, competitor, and product research within the Shopify and SaaS ecosystem to inform strategic direction.
• Stakeholder Management: Drive seamless communication and alignment between internal teams and external partners.
• Trusted Advisor: Maintain strict confidentiality and high ownership while handling ambiguous, complex business challenges.

Preferred Qualifications

• 3+ years of experience as a Chief of Staff, Strategy Consultant, or in a similar strategic role.
• Strong data-driven mindset with proven experience using Excel/Google Sheets, dashboards, and reporting tools.
• High proficiency with AI tools like ChatGPT, Notion AI, automation workflows, and prompt-based productivity.
• Exceptional written and verbal communication skills paired with strong stakeholder management abilities.
• Proven ability to operate in a fast-paced startup environment, taking high ownership of outcomes.
• Elite organizational skills, sharp attention to detail, and the ability to multitask seamlessly across competing priorities.
• Experience in ecommerce, SaaS, the Shopify ecosystem, or tech startups is a strong advantage.
• Comfortable working directly with founders and independently solving ambiguous, unstructured problems.

What We Offer

• Direct exposure to startup leadership and strategic decision-making.
• A high-impact role with a significant ownership and growth trajectory.
• The opportunity to work at the cutting-edge intersection of AI, ecommerce, and product execution.
• Competitive compensation with performance-driven growth opportunities.

We are a UK-based ecommerce company looking for a hands-on AI Automation & Integrations Engineer based in India to work directly with the founder.

Our goal is to progressively build an AI-first ecommerce operation by using AI, automation, APIs and software integrations to reduce manual work, improve decision-making and identify opportunities to increase revenue and profitability.

This is not a traditional data science or prompt engineering role. We are looking for a builder who can understand real business problems and turn them into reliable working systems.

What you will work on

• Build AI-powered automations and internal tools
• Connect ecommerce platforms and business systems through APIs and webhooks
• Build AI agents and LLM-powered workflows
• Automate repetitive operational processes
• Work with Shopify and ecommerce data
• Build automated reporting, alerts and business intelligence
• Develop inventory forecasting and operational tools
• Integrate AI with customer service, marketing, fulfilment and other business systems
• Identify new areas where AI and automation can improve efficiency, revenue or profitability
• Maintain and improve existing automations

Required skills

• Strong Python experience
• Strong understanding of REST APIs and webhooks
• Experience building software integrations and automations
• Practical experience using LLM APIs such as Claude, OpenAI or Gemini
• Experience working with databases such as PostgreSQL
• Git/GitHub
• Strong problem-solving ability
• Good written and spoken English
• Ability to work independently and take ownership of projects

Highly desirable

• n8n
• Shopify Admin API
• GraphQL
• JavaScript/TypeScript
• AI agents
• LangGraph/LangChain
• MCP
• AWS/GCP
• Ecommerce experience
• Data extraction/scraping
• Customer service or marketing integrations

We value real projects and practical ability more than certificates.

Candidates should be comfortable showing examples of AI automations, integrations, agents or software systems they have personally built.

Location: Remote, India

Experience: 3-7 years

Salary: ₹15-22 LPA depending on experience

Shivalik Design Pvt Ltd — GOTS-certified garment export house in Faridabad, Haryana, manufacturing for UK/EU brands. We are hiring for a full-time, on-site role in Faridabad.

About the role:

We are looking for an AI Automation Specialist to design and run no-code / low-code automation and AI-agent workflows that connect our factory, supply-chain and office systems.

What you'll do:

- Build automation workflows using no-code tools (n8n, Zapier, Make) and AI assistants.

- Integrate ChatGPT and Gemini APIs into recurring operational workflows (document handling, data extraction, summaries, alerts).

- Connect ERP, WhatsApp, Google Sheets, email and other tools used across factory operations.

- Own day-to-day monitoring, error-handling and iteration of automation runs.

- Translate operational requirements into working AI-agent flows and share runbooks.

What we're looking for:

- 1–3 years of hands-on no-code automation / AI-agent work.

- Practical experience with n8n, Zapier and Make.

- Working knowledge of ChatGPT and Gemini APIs and how to plug them into automation.

- Comfortable with spreadsheets, mail and WhatsApp integrations.

- Based in, or willing to relocate to, Faridabad (on-site, full-time).

Job Summary

•⁠ ⁠We are looking for a visionary technology leader responsible for driving the strategy, automation, and transformation of the enterprise IT operations landscape.

•⁠ ⁠This expanded role will oversee Service Improvement Initiatives and Adoption of AI -Ops & autonomous operations to deliver a self‑healing, predictive, and highly automated IT environment.

•⁠ ⁠This leader is accountable for significantly reducing manual support dependencies by implementing AI‑driven automation frameworks that eliminate L1 support (100%) and reduce L2 support effort by at least 50%, while ensuring world‑class performance, reliability, and security across IT services.

 Key Responsibilities:

1. Strategic & Autonomous Operations Leadership

•⁠ ⁠Define and execute a long-term strategy for AI, autonomous operations, and AI driven service management.

•⁠ ⁠Build /Operationalize an enterprise-wide framework for Autonomous IT Operations (AIOps), ensuring seamless integration with infrastructure, cloud, and SRE functions.

•⁠ ⁠Lead the implementation of AI agents, decisioning engines, and self-healing automation across service operations.

•⁠ ⁠Lead & drive Continual Service Improvement Programs across critical inhouse & partner managed Apps & Infra for higher availability on IT Side.

2. Operational Excellence & Automation Transformation

•⁠ ⁠Achieve 100% elimination of L1 support through predictive automation, intelligent routing, and autonomous resolution workflows.

•⁠ ⁠Deliver 50% reduction in L2 support workload through AI based diagnostics, automated remediations, and knowledge orchestration.

•⁠ ⁠Oversee implementation of AI driven monitoring, anomaly detection, auto triaging, and automated incident remediation.

•⁠ ⁠Optimize IT operations through AIOps, observability platforms, and closed loop automation.

3. Innovation & Technology Modernization

•⁠ ⁠Lead modernization of CI/CD, IaC, and DevSecOps with embedded AI and smart orchestration.

•⁠ ⁠Build a center of excellence for autonomous operations and AI first service engineering.

4. Incident, Problem & Change Management Automation

•⁠ ⁠Deploy automated playbooks, AI guided root cause analysis, and recommendation engines.

•⁠ ⁠Implement self-service and conversational AI capabilities across ITSM platforms.

•⁠ ⁠Ensure proactive detection (MTTD < 5 minutes) and rapid recovery (MTTR < 1 hour) through automation.

5. Stakeholder & Vendor Engagement

•⁠ ⁠Communicate operational health, transformation progress, AI impact, and risk posture to senior leadership.

•⁠ ⁠Partner with cybersecurity, product, and enterprise architecture teams to ensure secure and compliant autonomous operations.

•⁠ ⁠Manage strategic vendor partnerships for AI, observability, infrastructure, and automation technologies.

•⁠ ⁠Drive enterprise-wide AI adoption by conducting workshops and training sessions on AI platforms, identifying high-value business use cases, and acting as the bridge between IT teams and AI engineering. The role will champion AI awareness, translate IT needs into AI solutions, and ensure successful adoption and value realization.

Required Skills & Experience:

•⁠ ⁠Bachelor’s degree in engineering, Computer Science, or related field (B.E./BTech preferred).

•⁠ ⁠15+ years of progressive experience in infrastructure engineering, SRE, DevOps, and IT operations automation.

•⁠ ⁠Strong hands-on experience with AIOps platforms, Agentic AI models, and autonomous operations frameworks.

•⁠ ⁠Proven background in large scale IT modernization, observability, and reliability engineering.

•⁠ ⁠Expertise in cloud operations (AWS/Azure/OCI), Kubernetes, container orchestration etc.

•⁠ ⁠Deep understanding of AI/ML, automation platforms, scripting (Python/Shell), and integration pipelines.

•⁠ ⁠Experience with ITSM platforms, incident automation, and workflow orchestration.

•⁠ ⁠Strong leadership capabilities with experience in driving major automation transformations.

•⁠ ⁠Strong hands-on experience with AIOps platforms, Agentic AI models, and autonomous operations frameworks. 

•⁠ ⁠Knowledge on DevOps and SRE metrics and automation tools (Terraform, CloudFormation, Jenkins, Ansible, etc.).

About the company

We are an AI MSO that runs the administrative and billing work for independent physical therapy practices, from the first patient call to cash in the bank.

About the role

We are looking for an experienced AI engineer with hands-on experience in healthcare and revenue cycle management (RCM). You will build and deploy AI agents, automations and data workflows for healthcare operations, with a focus on the US market.

The work includes payer-portal automation for claim status and EOB retrieval, voice agents for payer follow-up, analysis of claim journeys and bottlenecks, and AI-assisted insights into practice performance. You will work directly with billing and operations teams, owning delivery from understanding the workflow through deployment, evaluation and ongoing improvement.

Responsibilities

• Own AI agent and automation workflows from requirements through design, development, deployment and monitoring.
• Build agents that work across payer portals, healthcare documents, practice-management systems, EHR-connected tools and voice channels.
• Turn fragmented healthcare data into validated, structured inputs for automation and analysis.
• Work directly with billing and operations teams to understand workflows, resolve exceptions and improve systems based on user feedback.
• Evaluate workflow accuracy and completion rates using representative test sets. Monitor failures and operating costs, and implement retries, exception queues and human escalation
• Implement approved privacy and security controls for sensitive healthcare data, including access restrictions, audit trails and safeguards against exposing patient information in logs or model inputs.
• Diagnose and improve failures across data ingestion, integrations, agent execution and user-facing workflows.
• Measure operational outcomes, such as time saved, reduced manual effort and faster turnaround, with the teams using the systems.

Who you are

You are a passionate and results-oriented engineer who is driven by the potential of AI/ML to revolutionize processes, enhance products, and ultimately improve user experiences. You thrive in dynamic environments and are comfortable navigating ambiguity. You possess a strong sense of ownership and are eager to take initiative, advocating for your technical decisions while remaining open to feedback and collaboration.

You are adept at working with real-world, often imperfect data, and have a proven ability to develop, refine, and deploy AI/ML models into production in a cost-effective and scalable manner. You are excited by the prospect of making US healthcare operations faster and more reliable, for the people who run them and the patients they serve.

Skills & Requirements

Must have

• At least 2 years of professional AI engineering experience, including deploying and supporting systems used in real operations. Internships and academic projects alone do not meet this requirement.
• Experience deploying and supporting an LLM-based application or AI agent in production, using capabilities such as retrieval-augmented generation (RAG), tool calling or multi-step workflows.
• Preferably has hands-on experience building AI or automation solutions for healthcare RCM workflows, such as claim status checks, accounts receivable follow-up, denial management, payment posting or payer interactions.
• Preferably has practical understanding of how billing teams work, how claims move through the revenue cycle, and how incomplete data and exceptions affect execution.
• Ability to explain your engineering contribution, how the system was evaluated, what failed and how you addressed it.
• Strong production Python and SQL skills, experience integrating APIs, and working knowledge of JavaScript/TypeScript for browser automation or application integration.
• Experience automating workflows across APIs, browsers or user interfaces, using tools such as Playwright, Selenium or UiPath, with error handling and human escalation where needed.
• Experience deploying and monitoring applications on at least one cloud platform—AWS, Azure or GCP—using containers, version control and automated testing.
• Experience handling imperfect inputs such as scanned PDFs, inconsistent portal layouts or incomplete records, with validation and exception handling.
• Experience working directly with billing or operations teams, improving systems based on their feedback, and demonstrating outcomes such as time saved, claims processed or reduced turnaround time.
• Experience handling sensitive healthcare data through appropriate access controls, secure logging and approved data-handling practices.

Preferred experience

• Experience delivering solutions for US healthcare providers, RCM companies or payer-facing operations, including working with US billing teams and payer workflows.
• Experience with practice-management or EHR integrations, payer portals, explanation of benefits (EOB) documents or electronic remittance advice (ERA) data.
• Experience analyzing claim histories, revenue-cycle bottlenecks or practice performance.
• Eperience building voice agents or integrating speech-to-text and text-to-speech services is a plus.
• Familiarity with Model Context Protocol (MCP) integrations.
• Experience with Kubernetes, serverless applications or event-driven architectures.

Working with us

We are a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

About the Role

We are a 25-year-old company building toward a technology-centered workforce where AI agents and automation handle more of the day-to-day work, supported by people with specialized expertise.

We are automating our existing workflows, expanding our use of agentic AI, launching a sister company next year, and building a fleet of Hermes AI agents to delegate and manage work.

We are looking for a hands-on AI Systems Architect & Company Technology Lead to help build, connect, and continuously improve these systems.

Key Responsibilities

·       Own and improve our Microsoft 365 technology environment and AI-powered workflows.

·       Build automations connecting email, meetings, Planner, and other business systems.

·       Research, test, implement, and maintain AI tools and integrations.

·       Build and manage the Hermes agent fleet, including shared memory, delegation rules, workflows, and reporting.

·       Connect AI agents to business systems and SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Help build an internal agentic marketing department by selecting and connecting the right AI tools.

·       Continuously troubleshoot, improve, and document our technology systems.

·       Help apply these systems as the company expands into new ventures.

Must-Haves

·       Strong technical problem-solving and self-teaching ability.

·       Solid hands-on experience building, configuring, and managing AI agents.

·       Experience connecting AI agents and multiple SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Comfortable with Python, JavaScript, or similar.

·       Ability to independently research, build, test, troubleshoot, and improve systems.

·       Strong interest in AI, automation, and emerging technology.

This is a rapidly changing field therefore Direct experience working with actual Hermes agents is not required. However, hands-on experience working with AI agents is required.

What we need is someone who already understands the fundamentals of deploying AI agents, giving them instructions and tools, connecting them to other systems, and making them work reliably in a real business environment.

The Opportunity

This is an opportunity to help us discover and implement what is actually possible with AI today, and to lead the process of expanding workflows along with the rapidly advancing capabilities — this role is not only to implement a technology that has already been figured out.

Director of Engineering (AI Solutions & Delivery)

About the Role

We are looking for a Director of Engineering to lead engineering execution and delivery across our enterprise AI solutions. This role combines strong engineering leadership with operational discipline, ensuring AI products move from technical design to production with predictable timelines, high quality, and reliable performance.

You will lead Engineering Managers and Tech Leads, oversee multiple engineering teams, and drive delivery excellence across AI-powered applications and platforms. The focus is on execution, technical quality, and organizational accountability, ensuring teams deliver scalable, production-ready AI systems without compromising reliability or engineering standards.

Key Responsibilities

1. Engineering Delivery & Execution

• Own engineering delivery schedules, translating product roadmaps into achievable sprint plans and release milestones.
• Establish measurable delivery targets, aiming for at least 85% on-time delivery across engineering teams.
• Identify and resolve cross-team dependencies, technical bottlenecks, and resource constraints before they affect delivery.
• Drive engineering process improvements across Agile development, CI/CD, automated testing, and release management.
• Monitor delivery metrics, sprint commitments, and release readiness to maintain predictable execution.

2. AI Quality, Evaluation & Governance

• Establish automated AI evaluation pipelines to measure hallucinations, relevance, groundedness, and contextual accuracy before production releases.
• Define quality benchmarks and evaluation criteria for LLM-powered applications and AI-driven workflows.
• Implement safety mechanisms, validation filters, circuit breakers, and human-in-the-loop fallbacks to manage unpredictable AI outputs.
• Oversee RAG pipelines, vector databases, data ingestion, and retrieval mechanisms to maintain accurate, reliable, and compliant context.
• Reduce production AI quality regressions through continuous evaluation, monitoring, and feedback loops.

3. Architecture, Scalability & Reliability

• Oversee the architecture of distributed systems and cloud-native applications to support scalability, availability, and performance.
• Drive reliability targets, including 99.9% uptime and low time-to-first-token (TTFT) latency for applicable AI applications.
• Partner with Staff and Principal Engineers to design resilient systems, including fallback mechanisms for model API failures, timeouts, and rate limits.
• Establish engineering standards for code reviews, observability, automated integration testing, and security compliance.
• Ensure production systems meet defined service-level objectives (SLOs) and performance benchmarks.

4. Engineering Leadership & Team Development

• Lead and develop Engineering Managers and Tech Leads, establishing clear ownership, accountability, and delivery expectations.
• Build a high-performance engineering culture focused on technical excellence, collaboration, and continuous improvement.
• Partner with Talent Acquisition to attract, assess, and hire strong software engineering and AI talent.
• Align engineering resources with business priorities, delivery commitments, and technical requirements.
• Address performance and execution challenges while maintaining team engagement and engineering quality.

Success Metrics: First 90 Days

First 30 Days

• Assess existing engineering workflows, delivery pipelines, and release processes.
• Establish baseline AI evaluation criteria and identify gaps in production quality.
• Take ownership of engineering delivery across teams and align expectations with Engineering Managers and Tech Leads.

First 60 Days

• Implement automated AI evaluation frameworks and establish measurable quality benchmarks.
• Improve cross-team coordination and resolve key delivery dependencies.
• Establish consistent sprint planning, release cadences, and delivery reporting.

First 90 Days

• Achieve at least 85% sprint commitment completion.
• Demonstrate measurable reductions in production AI quality regressions.
• Improve system reliability and stabilize latency against defined performance targets.
• Establish clear accountability and predictable delivery practices across engineering teams.

Qualifications & Requirements

• Experience: 14+ years in software engineering, including at least 5 years managing Engineering Managers or Tech Leads in enterprise or high-growth environments.
• AI/ML Expertise: Hands-on experience delivering AI-powered systems involving LLMs, RAG architectures, vector databases, prompt engineering, or model fine-tuning workflows.
• Engineering Delivery: Proven ability to lead multiple engineering teams and deliver complex technical initiatives from design through production launch.
• System Architecture: Experience with distributed systems, cloud-native backend infrastructure, and scalable APIs across AWS, GCP, or Azure.
• AI Quality & Reliability: Understanding of AI evaluation frameworks, production monitoring, hallucination mitigation, guardrails, and system reliability.
• Delivery Management: Strong experience with Agile methodologies, CI/CD, release planning, and engineering performance metrics.
• Leadership: Ability to establish accountability, manage competing priorities, and deliver against ambitious deadlines without compromising quality or team morale.

What Success Looks Like

The successful candidate will establish predictable engineering delivery, improve the quality and reliability of production AI systems, and build a culture of ownership across engineering teams. They will combine technical judgment with execution-focused leadership to ensure AI solutions are delivered on schedule, operate reliably, and meet enterprise expectations.

If you are passionate about building high-performing engineering teams and delivering enterprise-grade AI solutions at scale, we would like to hear from you.

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability.