AI Engineer / Forward Deployed Engineer

PPMI Construction Company

. Build and deploy AI solutions alongside researchers and clients in public policy analysis, consultancy and research .

Posted 9/28/2026full-timeVilnius • LithuaniaJunior💰 €2,500 - €3,800 per monthWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and deploying AI solutions, particularly in public policy analysis and research. Proficient in developing LLM applications, APIs, and analytical workflows while ensuring data protection and reproducibility.

Highest-signal resume keywords

Python ProgrammingJavaScript/TypeScript ExperienceAI Application DevelopmentAnalytical Workflow DesignPublic Policy Research Interest

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI Solutions DevelopmentMachine Learning ModelsData Science MethodsArchitectural EvaluationPrototyping and DeploymentPerformance ValidationAPI DevelopmentStatistical AnalysisTechnical Writing

Soft Skills

Proactive ApproachIndependent WorkCommunication Skills

Tools & Technologies

Agent HarnessesContext and Memory SystemsTool IntegrationsVersion ControlModel APIs

Industry Keywords

Public Policy AnalysisResearch MethodologiesData QualityEU InstitutionsDecision-Making Processes

Tech Stack

Tools & technologies

JavaScriptPythonTypeScript

About the role

Key responsibilities & impact

Build and deploy AI solutions alongside researchers and clients in public policy analysis, consultancy and research
Build LLM applications and agentic workflows, including agent harnesses, context and memory systems, tool integrations and orchestration, with appropriate permissions and human oversight
Define problems and evaluate architectural approaches such as agentic RAG, GraphRAG, vector search, single-agent or multi-agent systems, and post-training methods
Select approaches balancing research and business needs with task quality, reliability, complexity and cost
Turn prototypes into reliable, deployable tools
Develop pipelines, APIs and interfaces
Validate performance and failure handling on realistic research tasks
Ensure data protection, reproducibility and monitoring
Maintain and improve deployed solutions through user feedback
Work with policy researchers to apply AI and data science methods to research questions
Validate results against expert judgement and simpler methods
Preserve source references and reproducible workflows
Contribute to analytical reports and evaluation methodologies
Work with clients and project teams to understand needs, define requirements and success criteria
Demonstrate tools, gather feedback, support adoption and contribute to technical proposals and clear policy-relevant findings

Requirements

What you’ll need

Degree in computer science, artificial intelligence, data science, statistics, computational social sciences, economics or a related field; equivalent practical experience is welcome when supported by relevant skills and projects
1–3 years of practical experience building and testing AI applications, ML models, or analytical workflows in professional or similarly substantial project settings
Ability to explain contributions, evaluation methods, trade-offs and improvements
Strong working knowledge of Python
Experience working with JavaScript/TypeScript
Interest in public policy and research, including research questions, data quality and limits of analysis
Proactive approach and drive to experiment
Ability to follow AI research, model releases and developer tools and evaluate relevant advances
Ability to work independently and own work end to end
Full English proficiency
Excellent technical writing skills
Nice to have, not essential: experience with agent harnesses, context, memory, tools, retrieval or orchestration
Nice to have, not essential: familiarity with model APIs, MCP tool integrations, structured outputs, evaluations, execution traces, version control, permissions and reliable deployment
Nice to have, not essential: familiarity with policy evaluation, EU institutions and decision-making processes

Benefits

Comp & perks

Significant autonomy and dedicated time for experimentation
Training and coaching
Practical experimentation, training and feedback across AI engineering, machine learning, policy research methods, data science, cloud services and project delivery
No fixed office hours
Remote-working options; for office-based employees, remote work is available for up to half of the time
Private employee health insurance*
Extra days off
Access to the Mindletic Emotional Intelligence Training App
Meaningful impact through work addressing societal challenges
*For office-based employees.