🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
About Indicium AI Indicium AI is trusted by the world's leading enterprises to deliver AI into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from AI with unmatched clarity, speed, and capability. Powered by 600+ AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners - including Anthropic, Databricks, AWS, OpenAI, and Microsoft - to deliver modern AI with speed and measurable impact. Overview We're seeking an experienced AI Engineer to design, build, and deploy production-grade AI systems powered by large language models. This role sits at the intersection of software engineering and AI implementation, focusing on building reliable, scalable applications rather than model training or research. You'll work with cutting-edge LLM technologies, building advanced AI systems that solve complex real-world problems through multi-agent orchestration, intelligent tool integration, and robust production workflows. You'll be crafting the orchestration layer that makes these systems production-ready—handling failure modes, optimizing agent collaboration, and ensuring consistent, reliable outputs at scale. You’ll combine strong software engineering fundamentals with deep practical knowledge of LLM capabilities, limitations, and best practices for building non-deterministic systems that users can trust. Responsibilities Design and implement production AI systems integrating LLMs, RAG pipelines, vector databases, and agentic frameworks. Create evaluation frameworks to measure and monitor system performance, accuracy, and reliability Build and maintain production-grade AI applications with clean code, appropriate error handling, APIs, and data pipelines Experience implementing, maintaining and evaluating retrieval systems (vector/graph databases, ingestion pipelines, chunking strategies, retrieval techniques such as HyDE) Implement feedback loops and observability to continuously improve system performance Craft effective prompts and optimize for latency, cost, and quality across different model providers and configurations Required Skills and Experience Hands-on experience building applications with LLM APIs and deep understanding of their capabilities, limitations, and failure modes Practical implementation of RAG architectures, vector databases, knowledge graphs and prompt engineering Experience building multi-step LLM workflows and agentic systems using frameworks (e.g. SDK, Strands, Claude Agents SDK, LangGraph, etc.) or custom implementations where needed Strong Python (or other modern programming language) proficiency with production API/service development experience and cloud platform knowledge (AWS, GCP, Azure) Understanding of distributed systems, CI/CD, testing frameworks, and deployment pipelines Solid foundations and understanding of production-grade, cloud-native platform and infrastructure requirements, design, and implementation. Strong data manipulation skills (pandas, SQL) and understanding of evaluation strategies for LLM-based systems Ability to work with ambiguity and optimise non-deterministic systems through a process of experimentation and evaluation while balancing latency/cost/quality tradeoffs Nice to Have Experience with AI-assisted coding using tools like Claude Code, OpenAI Codex, Github Copilot Experience with fine-tuning LLMs for domain-specific applications and knowledge of when fine-tuning is preferable to prompt engineering or RAG Experience with real-time streaming, multimodal models, or search technologies like Elasticsearch Familiarity with model observability tools (LangSmith, Weights & Biases) and cost optimization strategies Experience in specialized verticals (financial services, energy, healthcare, legal, retail) with understanding of compliance, security, and responsible AI practices Experience with setting up tool calling agents, handoffs, and guardrails Why Indicium AI Fast-growing start-up organisation with huge opportunity for career growth Highly competitive salary package along with company bonus A hugely collaborative working environment where every person’s viewpoint is considered - a chance to make your mark on the business from day one! Financially backed business meaning security and support for new initiatives and global market expansion Pick your own Gear! Macbooks, PCs, Accessories! Drive your development with a personal learning budget Benefits Holiday Entitlement - 25 days holiday plus bank holidays Learning & Development: 1.500€ training budget + 5 training days Company Bonus - Discretionary company and personal bonus paid quarterly Pension Scheme Choose Your Kit - Select from a range of laptops and accessories Social Events: meeting - Ups, Squad events, Summer/ Christmas events, etc. And many others.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.