Lead AI Engineer
Indicium AI Lisbon, Portugal
Looking for a Hybrid Remote AI role? Lead AI Engineer at Indicium AI is listed on Makely Remote Jobs as a Full-time opening based in Lisbon, Portugal (Worldwide). Review the role overview below, then apply on the employer’s original listing — Makely Remote Jobs does not process applications.
Role overview
At Indicium AI (Permanent), in Lisbon, Portugal
Expires at: 2026-12-01
Remote policy: Partial remote
Expires at: 2026-12-01
Remote policy: Partial remote
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
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
Main requirements
- 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
- Strong written and spoken English and Portuguese.
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
Benefits & Perks
Why Indicium AI
- Plentiful opportunity and support for learning & development; £2k annual training budget (with 5 study days), access to Udemy, external consulting & leadership skills training
- Fast-growing start-up organisation with huge opportunity for career growth
- Competitive salary package along with company annual 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!
- Strong engineering community; regularly run forums and Lunch & Learns, internal technology practices, we host external meet-ups
- Financially backed business meaning security and support for new initiatives and global market expansion
- Pick your own Gear! Macbooks, PCs, Accessories!
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.
Summary provided for discovery. Always confirm details and apply on the original source. Makely Remote Jobs is not the employer and does not process applications.
Frequently asked questions
Is Lead AI Engineer at Indicium AI a remote job?
Yes. This listing is categorized as Hybrid Remote on Makely Remote Jobs. Confirm any location or timezone limits in the original posting before you apply.
What is the employment type for Lead AI Engineer?
Source data lists this as Full-time. Always verify the contract type, benefits, and start date on the employer’s application page.
Where is Lead AI Engineer located?
Listed location: Lisbon, Portugal. Many remote AI roles allow work-from-home with country or timezone restrictions — check the full description.
Do I apply on Makely Remote Jobs?
No. Makely Remote Jobs aggregates public remote job feeds for discovery. Use “Apply on Original Site” to open the employer’s official application URL. We never host applications or collect resumes.
Does Indicium AI list salary for this AI role?
Salary was not published in the source feed. Check the original listing or ask the recruiter during screening for compensation details.